000			04268nab|a22005297a|4500
001			69506
003			MX-TxCIM
005			20251215154743.0
008			202510s2025||||sz |||p|op||||00||0|eng|d
022			_a1664-462X
024	8		_ahttps://doi.org/10.3389/fpls.2025.1675993
040			_aMX-TxCIM
041			_aeng
100	1		_aSaavedra-Avila, J.I. _938567
245	1	0	_aUnraveling the genetic basis of general combining ability in CIMMYT elite bread wheat germplasm : _bimplications for breeding strategies optimization
260			_aSwitzerland : _bFrontiers Media, _c2025.
500			_aPeer review
500			_aOpen Access
520			_aIn wheat breeding programs, several hundred crosses are performed annually, but only individuals from a few families advance to the final stages of the breeding pipelines. Therefore, a deeper understanding of the general combining ability (GCA) of wheat genotypes might enhance the breeding efficiency in selecting parents. For this reason, we tested the performance of the offspring of similar to 1200 parental elite lines. Using a genome-wide association study (GWAS), gene ontology (GO) analysis, and genomic prediction (GP), our objectives were to i) identify marker-trait associates (MTAs) and candidate genes, ii) assess temporal allele frequency dynamics of identified MTAs, and iii) estimate prediction accuracy (PA) for key traits: Progeny Number per-Cross (PNC), grain yield (GY), and a combined index incorporating these traits ("index"). Our findings revealed a total of 13 MTAs: eight for GY, four for the "index", and one for PNC. The GO analysis highlighted several genes involved in hydrogen peroxide metabolism and catabolism processes (H2O2), reactive oxygen species, response to oxidative stress, cell wall biogenesis, the metabolic process of modified amino acids at the cellular level, and glutathione metabolic process for the studied traits. Notably, allele frequency analysis over time indicated that most MTAs are under positive selection, likely reflecting indirect breeder-driven selection. The highest PA was reached by using the reproducing kernel Hilbert space (RKHS) model for the trait GY (0.34). The identification of MTAs for PNC and GY provided insight into the biological pathways underpinning combining ability and demonstrated the potential for predicting the ability of the genotypes to be crossed. These findings might contribute to the optimization crossing strategy saving costs and increasing the breeding program efficiency.
546			_aText in English
591			_aSaavedra-Avila, J.I. : Not in IRS staff list but CIMMYT Affiliation
597			_aNutrition, health & food security _aClimate adaptation & mitigation _bAccelerated Breeding _cGenetic Innovation _dCGIAR Trust Fund _uhttps://hdl.handle.net/10568/178354 _fBreeding for Tomorrow
610	2	0	_aCIMMYT _939008
650		7	_aWheat _2AGROVOC _91310
650		7	_aBreeding _2AGROVOC _91029
650		7	_aCombining ability _2AGROVOC _92367
650		7	_aGenome-wide association studies _2AGROVOC _931443
650		7	_aForecasting _2AGROVOC _92701
650		7	_aEfficiency _2AGROVOC _94390
700	1		_aGerard, G.S. _81713398 _gGlobal Wheat Program _911490
700	1		_aEsposito, S. _933033
700	1		_aVelu, G. _gGlobal Wheat Program _8INT2983 _9880
700	1		_aHuerta-Espino, J. _gGlobal Wheat Program _8CHUE01 _9397
700	1		_aTarekegn, Z.T. _8001713397 _gGlobal Wheat Program _931150
700	1		_aDreisigacker, S. _gGlobal Wheat Program _8INT2692 _9851
700	1		_aSaint Pierre, C. _gGlobal Wheat Program _8INT2731 _9855
700	1		_aPacheco Gil, R.A. _8N1705917 _gGenetic Resources Program _96455
700	1		_aToledo, F.H. _gGenetic Resources Program _8I1706676 _91999
700	1		_aGardner, K.A. _8001712617 _gGenetic Resources Program _917393
700	1		_aCrespo-Herrera, L.A. _gGlobal Wheat Program _8I1706538 _92608
700	1		_aCrossa, J. _gGenetic Resources Program _8CCJL01 _959
700	1		_8001713327 _aVitale, P. _gGenetic Resources Program _931497
773	0		_tFrontiers in Plant Science _gv. 16, art. 1675993 _dSwitzerland : Frontiers Media, 2025 _x1664-462X _w56875
856	4		_yOpen Access through DSpace _uhttps://hdl.handle.net/10883/36164
942			_cJA _n0 _2ddc
999			_c69506 _d69498