**Author details**

introgression of resistance genes to susceptible germplasm. However, our results indicated a low genetic effect of the QTL detected in BAT 477. Therefore, a more intensive searching of significant QTLs is needed. Genetic map development allows identification and use of genes and genomic regions (QTLs) with economic interest and then develops markerassisted selection (MAS) strategies [25]. Vallejos et al. [26] performed the first gene map of common beans using morphologic, isozymes and RFLP markers. Then, Schneider et al. [27] identified 16 QTLs associated with *F. solani* f. sp. *phaseoli* resistance in F4:6 RILs derived from Montcalm (susceptible) x FR266 (resistant). These QTLs were mainly found on LGs 2 and 5, and seven QTLs explained 64% of disease resistance. Chowdhury et al. [28] identified two QTLs associated with FSP resistance and explaining 50% of phenotypic variance using F2:6 RILs from AC Compass (susceptible) × NY2114–12 (resistant), while Román-Avilés et al. [29] identified nine QTLs associated with resistance to FSP in F4:5 inbred backcross populations from Red Hawk (susceptible) × NG San Luis (Resistant) and C97407 (susceptible) × NG San Luis, which explained from 5 to 53% of phenotype variation and located mainly at

114 Fusarium - Plant Diseases, Pathogen Diversity, Genetic Diversity, Resistance and Molecular Markers

We found significant genetic variability in FSP isolates from Aguascalientes and other regions of México although no clear association among morphology, pathogenicity or AFLP genotype

Under field conditions, we found high variation on reactions to FSP root rots; resistance was more frequent on black seed-coated beans, while susceptibility was common in pinto beans. We found a greater variation on root rot severity disease in Aguascalientes when compared with State of México, while an opposite response on grain yields was found

One QTL with low variance explanation of FSP resistance in BAT 477 was found; therefore, more intensive searching of significant QTLs is needed to improve marker-assisted selection

Most of the results reported in this chapter are derived from B. Sc. (K. Lira-Méndez, UA Tamaulipas; M. Martínez-Garnica, UA Aguascalientes); M. Sc. (M. Martinez-Garnica, IT Aguascalientes) and Dr. Sci. (R.Méndez-Aguilar, CICATA Altamira-IPN) theses. COSNET-SEP and CONACYT supported graduate studies of MMG and RMA. This work was supported by International Foundation for Science (grant no. AC/3201-1) from Stockholm, Sweden; COSNET-DGETA-SEP; Instituto Politécnico Nacional (grant no. 1350) and CONACYT-Ciencia Básica (grants no. 48457-Z and no. 176282). JSPR, RRS, FJIP, RMA & NMP are SNI

LGs 1 and 7.

was detected.

across locations.

**Acknowledgements**

strategies in common beans for México.

scholars, and SHD is EDI-IPN and COFAA-IPN scholar.

**5. Conclusions**

José Saul Padilla-Ramírez1 , Roberto Ochoa-Márquez1 , Rigoberto Rosales-Serna1 , Francisco J. Ibarra-Pérez1 , Reinaldo Méndez-Aguilar1 , Sanjuana Hernández-Delgado2 , José Luis Chávez-Servia3 and Netzahualcoyotl Mayek-Pérez2,4\*

\*Address all correspondence to: nmayek@ipn.mx

1 Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias (INIFAP), Ciudad de México, Mexico

2 Centro de Biotecnología Genómica-Instituto Politécnico Nacional, Reynosa, Tamaulipas, México

3 CIIDIR-Unidad Oaxaca, Instituto Politécnico Nacional, Oaxaca, México

4 Universidad México Americana del Norte A.C., Reynosa, México
