Molecular dissection of connected rice populations revealed important genomic regions for agronomic and biofortification traits

Alvin D Palanog; Chau Thanh Nha; Gwen Iris L Descalsota-Empleo; Mark Ian Calayugan; Zin Mar Swe; Amery Amparado; Mary Ann Inabangan-Asilo; Jose E Hernandez; Pompe C Sta Cruz; Teresita H Borromeo; Antonio G Lalusin; Ramil Mauleon; Kenneth L McNally; B P Mallikarjuna Swamy

doi:10.3389/fpls.2023.1157507

Molecular dissection of connected rice populations revealed important genomic regions for agronomic and biofortification traits

Front Plant Sci. 2023 Mar 22:14:1157507. doi: 10.3389/fpls.2023.1157507. eCollection 2023.

Authors

Alvin D Palanog^{1

2

3}, Chau Thanh Nha⁴, Gwen Iris L Descalsota-Empleo⁵, Mark Ian Calayugan², Zin Mar Swe¹, Amery Amparado¹, Mary Ann Inabangan-Asilo¹, Jose E Hernandez², Pompe C Sta Cruz², Teresita H Borromeo², Antonio G Lalusin², Ramil Mauleon^{1

5}, Kenneth L McNally¹, B P Mallikarjuna Swamy¹

Affiliations

¹ Rice Breeding Innovations Platform, International Rice Research Institute, Los Baños, Laguna, Philippines.
² College of Agriculture and Food Science, University of the Philippines, Los Baños, Laguna, Philippines.
³ PhilRice Negros Branch Station, Philippine Rice Research Institute, Murcia, Negros Occidental, Philippines.
⁴ Cant Ho University, Cant Ho, Vietnam.
⁵ College of Agriculture, University of Southern Mindanao, Kabacan, North Cotabato, Philippines.

Abstract

Breeding staple crops with increased micronutrient concentration is a sustainable approach to address micronutrient malnutrition. We carried out Multi-Cross QTL analysis and Inclusive Composite Interval Mapping for 11 agronomic, yield and biofortification traits using four connected RILs populations of rice. Overall, MC-156 QTLs were detected for agronomic (115) and biofortification (41) traits, which were higher in number but smaller in effects compared to single population analysis. The MC-QTL analysis was able to detect important QTLs viz: qZn_5.2, qFe_7.1, qGY_10.1, qDF_7.1, qPH_1.1, qNT_4.1, qPT_4.1, qPL_1.2, qTGW_5.1, qGL_3.1 , and qGW_6.1 , which can be used in rice genomics assisted breeding. A major QTL (qZn_5.2 ) for grain Zn concentration has been detected on chromosome 5 that accounted for 13% of R². In all, 26 QTL clusters were identified on different chromosomes. qPH_6.1 epistatically interacted with qZn_5.1 and qGY_6.2 . Most of QTLs were co-located with functionally related candidate genes indicating the accuracy of QTL mapping. The genomic region of qZn_5.2 was co-located with putative genes such as OsZIP5, OsZIP9, and LOC_OS05G40490 that are involved in Zn uptake. These genes included polymorphic functional SNPs, and their promoter regions were enriched with cis-regulatory elements involved in plant growth and development, and biotic and abiotic stress tolerance. Major effect QTL identified for biofortification and agronomic traits can be utilized in breeding for Zn biofortified rice varieties.

Keywords: QTL; Zn; biofortification; candidate genes; connected populations; micronutrients; rice.

Grants and funding

The work was supported by HarvestPlus (5402), Bill and Melinda Gates Foundation (OPP1194925), Department of Science and Technology (DOST) - Philippines. The funding entities did not influence the design, data collection, and interpretation, and write-up of the paper.