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Record W4291650684 · doi:10.1101/2022.08.13.502796

CGIAR BARLEY BREEDING TOOLBOX: A diversity panel to facilitate breeding and genomic research in the Developing World

2022· preprint· en· W4291650684 on OpenAlexaffabout
Outmane Bouhlal, Andrea Visioni, R. P. S. Verma, M. Kandil, Sanjaya Gyawali, F. Capettini, Miguel Sanchez‐Garcia

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsOlds College
FundersArab Fund for Economic and Social DevelopmentConsortium of International Agricultural Research CentersU.S. Department of Agriculture
KeywordsGermplasmBiologyGenetic diversityGenotypingBiotechnologyGenotypeGeneticsSNP genotypingPlant breedingPopulationGeographyAgronomyGeneDemography

Abstract

fetched live from OpenAlex

Abstract Despite the reduced cost of the new genotyping technologies, many public and private breeding programs, mostly in developing countries, still cannot afford them, hindering their research. The objective of the present study was to identify and assemble an Association Mapping panel of widely diverse barley genotypes to serve as a barley breeding toolbox, especially for the Developing World. The main criteria were: i) to be representative of the germplasm grown in the Developing World; ii) to cover a wide range of genetic variability and iii) to be of public domain. For it, we assembled and genotyped a Global Barley Panel (GBP) of 530 genotypes representing a wide range of row-types, end-uses, growth habits, geographical origins and environmental conditions. The GBP accessions were genotyped using the barley Infinium iSelect 50K chip. A total of 40,342 SNP markers were polymorphic and displayed an average polymorphism information content (PIC) of 0.35, with 66% of them exceeding PIC=0.25. The analysis of the population structure identified 8 sub-populations mostly linked to the geographical origin of the lines (Europe, Australia, USA, Canada, Africa, Latin-America, ICARDA and others), four of them of significant ICARDA origin. The 16 allele combinations at 4 major flowering genes (HvVRN-H3, HvPPD-H1, HvVRN-H1 and HvCEN) explained 11.07% genetic variation and were linked to the geographic origins of the lines studied. Among origins, ICARDA material (n= 257) showed wide diversity as revealed by the highest number of polymorphic loci (99.76% of all polymorphic SNPs in GBP), number of private alleles and Nei’s gene diversity and the fact that ICARDA lines were present in all 8 sub-populations and carried all 16 allelic combinations at phenology genes. Due to their genetic diversity and their representativity of the germplasm adapted to the Developing World, 312 ICARDA lines and cultivated landraces were pre-selected to form the CGIAR Barley Breeding Toolbox (CBBT). Using the genotypic data and the Mean of Transformed Kinships method, we assembled the CBBT, an Association Mapping panel of 250 accessions capturing most of the allelic diversity in the global panel. The CBBT preserves a good balance between row types as well as a good representation of both allelic combinations identified at most important phenological loci and sub-populations of the GBP. The CBBT lines together with their genotypic data will be made available to breeders and researchers worldwide to serve as a collaborative tool to underpin the genetic mechanisms of traits of interest for barley cultivation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.156
GPT teacher head0.264
Teacher spread0.108 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2022
Admission routes2
Has abstractyes

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