Literature DB >> 27889500

Enhancing phosphorus uptake efficiency through QTL-based selection for root system architecture in maize.

Riliang Gu1, Fanjun Chen2, Lizhi Long2, Hongguang Cai3, Zhigang Liu2, Jiabo Yang2, Lifeng Wang4, Huiyong Li5, Junhui Li6, Wenxin Liu6, Guohua Mi2, Fusuo Zhang2, Lixing Yuan7.   

Abstract

Root system architecture (RSA) plays an important role in phosphorus (P) acquisition, but enhancing P use efficiency (PUE) in maize via genetic manipulation of RSA has not yet been reported. Here, using a maize recombinant inbred line (RIL) population, we investigated the genetic relationships between PUE and RSA, and developed P-efficient lines by selection of quantitative trait loci (QTLs) that coincide for both traits. In low-P (LP) fields, P uptake efficiency (PupE) was more closely correlated with PUE (r = 0.48-0.54), and RSA in hydroponics was significantly related to PupE (r = 0.25-0.30) but not to P utilization efficiency (PutE). QTL analysis detected a chromosome region where two QTLs for PUE, three for PupE and three for RSA were assigned into two QTL clusters, Cl-bin3.04a and Cl-bin3.04b. These QTLs had favorable effects from alleles derived from the large-rooted and high-PupE parent. Marker-assisted selection (MAS) identified nine advanced backcross-derived lines carrying Cl-bin3.04a or Cl-bin3.04b that displayed mean increases of 22%-26% in PUE in LP fields. Furthermore, a line L224 pyramiding Cl-bin3.04a and Cl-bin3.04b showed enhanced PupE, relying mainly on changes in root morphology, rather than root physiology, under both hydroponic and field conditions. These results highlight the physiological and genetic contributions of RSA to maize PupE, and provide a successful study case of developing P-efficient crops through QTL-based selection. Copyright Â
© 2016 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Maize; Marker-assisted selection; Phosphorus; Quantitative trait loci; Root system architecture

Mesh:

Substances:

Year:  2016        PMID: 27889500     DOI: 10.1016/j.jgg.2016.11.002

Source DB:  PubMed          Journal:  J Genet Genomics        ISSN: 1673-8527            Impact factor:   4.275


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