UMR DIADE

DIversity - Adaptation - plant DEvelopment

The DIADE Research Unit aims to understand the diversification of tropical plants, one of the main original reservoirs of biodiversity, and for which conservation, management and exploitation are an important issue for Sustainable Development.

The nine teams forming the Unit belong to IRD, University of Montpellier, CIRAD, and CNRS.

CERES Team

DYNADIV Team

PANEEC Team

EVOGEC Team

ADvENS Team

AgroLD

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21 to 30 of 1,043 Results

climatemetrics_mil173Landraces_EWEMBI_Liebmann_1979-1990.tab Sep 17, 2025 - Testing the impact of environmental variables on the predictive performance of genomic offset statistics: crop-specific metrics computed from the EWEMBI v.1 climate dataset. Tabular Data - 508.5 KB - 185 Variables, 173 Observations - UNF:6:EdX+/x3auhCXDY0Q7OgZ4g== Données Precipatation, Temperature and radiation crop-specific climate variables computed and extracted from the EWEMBI (V1) dataset, for 173 populations of pearl millet.
Dictionary_cropmetrics.pdf Sep 17, 2025 - Testing the impact of environmental variables on the predictive performance of genomic offset statistics: crop-specific metrics computed from the EWEMBI v.1 climate dataset. Adobe PDF - 25.0 KB - MD5: baaa5328ffa5ac93176b65b0d2789aa8 Documentation Dictionary of crop climate metrics
extract_pixels_from_netcdf.py Sep 17, 2025 - Testing the impact of environmental variables on the predictive performance of genomic offset statistics: crop-specific metrics computed from the EWEMBI v.1 climate dataset. Python Source Code - 6.7 KB - MD5: bebbb223232f0f478feb8cdcd2685b46 Code A python script that extracts crop-specific metrics from the netCDF file, with a passport file containing geographical coordinates.
ReadMe_M9YGDC.txt Sep 17, 2025 - Testing the impact of environmental variables on the predictive performance of genomic offset statistics: crop-specific metrics computed from the EWEMBI v.1 climate dataset. Plain Text - 1.8 KB - MD5: b4beefe745809f4a1f5ca15b1dba090f Documentation Contains citation, description and conditions of use of dataset data
Development of new microsatellites markers for Cola acuminata (Malvaceae), a socio-economically important fruit tree species in Central Africa Aug 27, 2025 - DYNADIV Team Duminil, Jerome; Dupiol, Pablo; Chakocha Ngandjui, Armel Franklin; Tientcheu, Avana Marie Louise; Mariac, Cedric; Charahabil, Mohamed Mahamoud; Barnaud, Adeline, 2025, "Development of new microsatellites markers for Cola acuminata (Malvaceae), a socio-economically important fruit tree species in Central Africa", https://doi.org/10.23708/6FCSLF, DataSuds, V1, UNF:6:JjyY2CKXXeBPZvLKRN5hnA== [fileUNF] Data from the publication "Development of new microsatellites markers for Cola acuminata (Malvaceae), a socio-economically important fruit tree species in Central Africa". Manuscript PJS_2_147801 Plant Ecology and Evolution. We developed a new set of nuclear microsatellite marker...
ReadMe_6FCSLF.txt Aug 27, 2025 - Development of new microsatellites markers for Cola acuminata (Malvaceae), a socio-economically important fruit tree species in Central Africa Plain Text - 1.3 KB - MD5: 74d25aa64ab14373c48e4b570ee3bd57 Documentation Contains citation, description and conditions of use of dataset data
data_dictionnary.tab Aug 27, 2025 - Development of new microsatellites markers for Cola acuminata (Malvaceae), a socio-economically important fruit tree species in Central Africa Tabular Data - 390 B - 2 Variables, 5 Observations - UNF:6:JkE4eofLBJ/AAoTufZI0Nw== Documentation Data dictionnary
Data_file_SSR_ColaAcuminata_Cameroun_Spagedi.tab Aug 27, 2025 - Development of new microsatellites markers for Cola acuminata (Malvaceae), a socio-economically important fruit tree species in Central Africa Tabular Data - 22.0 KB - 19 Variables, 189 Observations - UNF:6:bRR1Skfg9oIKXzD54ax9Gw== Données Data file
VCF files from the study of low recombining genomic regions in pearl millet Jun 23, 2025 - DYNADIV Team Salson, Marine; Duranton, Maud; Huynh, Stella; Mariac, Cédric; Tranchant-Dubreuil, Christine; Orjuela, Julie; Cubry,Philippe; Thuillet, Anne-Celine; Burgarella, Concetta; De Navascués, Miguel; Zekraouï, Leïla; Couderc, Marie; Arribat, Sandrine; Rodde, Nathalie; Barnaud, Adeline; Adama Faye; Kane, Ndjido; Vigouroux, Yves; Berthouly-Salazar, Cécile, 2025, "VCF files from the study of low recombining genomic regions in pearl millet", https://doi.org/10.23708/SN2T4A, DataSuds, V1 We conducted a comprehensive investigation of large low-recombining regions in cultivated populations of pearl millet, an outcrossing diploid African cereal. We adopted a population genomic approach based on the analysis of single nucleotide polymorphisms. The repository contains...
ReadMe_SN2T4A.txt Jun 23, 2025 - VCF files from the study of low recombining genomic regions in pearl millet Plain Text - 2.0 KB - MD5: 8f93a5fcb1e298749d0b547f19f85602 Documentation Contains citation, description and conditions of use of dataset data

climatemetrics_mil173Landraces_EWEMBI_Liebmann_1979-1990.tab

Sep 17, 2025 - Testing the impact of environmental variables on the predictive performance of genomic offset statistics: crop-specific metrics computed from the EWEMBI v.1 climate dataset.

Tabular Data - 508.5 KB - 185 Variables, 173 Observations -

Données

Precipatation, Temperature and radiation crop-specific climate variables computed and extracted from the EWEMBI (V1) dataset, for 173 populations of pearl millet.

Dictionary_cropmetrics.pdf

Sep 17, 2025 - Testing the impact of environmental variables on the predictive performance of genomic offset statistics: crop-specific metrics computed from the EWEMBI v.1 climate dataset.

Adobe PDF - 25.0 KB -

Documentation

Dictionary of crop climate metrics

extract_pixels_from_netcdf.py

Sep 17, 2025 - Testing the impact of environmental variables on the predictive performance of genomic offset statistics: crop-specific metrics computed from the EWEMBI v.1 climate dataset.

Python Source Code - 6.7 KB -

Code

A python script that extracts crop-specific metrics from the netCDF file, with a passport file containing geographical coordinates.

ReadMe_M9YGDC.txt

Sep 17, 2025 - Testing the impact of environmental variables on the predictive performance of genomic offset statistics: crop-specific metrics computed from the EWEMBI v.1 climate dataset.

Plain Text - 1.8 KB -

Documentation

Contains citation, description and conditions of use of dataset data

Development of new microsatellites markers for Cola acuminata (Malvaceae), a socio-economically important fruit tree species in Central Africa

Aug 27, 2025 - DYNADIV Team

Duminil, Jerome; Dupiol, Pablo; Chakocha Ngandjui, Armel Franklin; Tientcheu, Avana Marie Louise; Mariac, Cedric; Charahabil, Mohamed Mahamoud; Barnaud, Adeline, 2025, "Development of new microsatellites markers for Cola acuminata (Malvaceae), a socio-economically important fruit tree species in Central Africa", https://doi.org/10.23708/6FCSLF, DataSuds, V1, UNF:6:JjyY2CKXXeBPZvLKRN5hnA== [fileUNF]

Data from the publication "Development of new microsatellites markers for Cola acuminata (Malvaceae), a socio-economically important fruit tree species in Central Africa". Manuscript PJS_2_147801 Plant Ecology and Evolution. We developed a new set of nuclear microsatellite marker...

ReadMe_6FCSLF.txt

Aug 27, 2025 - Development of new microsatellites markers for Cola acuminata (Malvaceae), a socio-economically important fruit tree species in Central Africa

Plain Text - 1.3 KB -

Documentation

Contains citation, description and conditions of use of dataset data

data_dictionnary.tab

Aug 27, 2025 - Development of new microsatellites markers for Cola acuminata (Malvaceae), a socio-economically important fruit tree species in Central Africa

Tabular Data - 390 B - 2 Variables, 5 Observations -

Documentation

Data dictionnary

Data_file_SSR_ColaAcuminata_Cameroun_Spagedi.tab

Aug 27, 2025 - Development of new microsatellites markers for Cola acuminata (Malvaceae), a socio-economically important fruit tree species in Central Africa

Tabular Data - 22.0 KB - 19 Variables, 189 Observations -

Données

Data file

VCF files from the study of low recombining genomic regions in pearl millet

Jun 23, 2025 - DYNADIV Team

Salson, Marine; Duranton, Maud; Huynh, Stella; Mariac, Cédric; Tranchant-Dubreuil, Christine; Orjuela, Julie; Cubry,Philippe; Thuillet, Anne-Celine; Burgarella, Concetta; De Navascués, Miguel; Zekraouï, Leïla; Couderc, Marie; Arribat, Sandrine; Rodde, Nathalie; Barnaud, Adeline; Adama Faye; Kane, Ndjido; Vigouroux, Yves; Berthouly-Salazar, Cécile, 2025, "VCF files from the study of low recombining genomic regions in pearl millet", https://doi.org/10.23708/SN2T4A, DataSuds, V1

We conducted a comprehensive investigation of large low-recombining regions in cultivated populations of pearl millet, an outcrossing diploid African cereal. We adopted a population genomic approach based on the analysis of single nucleotide polymorphisms. The repository contains...

ReadMe_SN2T4A.txt

Jun 23, 2025 - VCF files from the study of low recombining genomic regions in pearl millet

Plain Text - 2.0 KB -

Documentation

Contains citation, description and conditions of use of dataset data

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