Genetic variation among elite inbred lines suggests potential to breed for BNI-capacity in maize

Abstract

Biological nitrification inhibition (BNI) is a plant function where root systems release antibiotic compounds (BNIs) specifically aimed at suppressing nitrifiers to limit soil-nitrate formation in the root zone. Little is known about BNI-activity in maize (Zea mays L.), the most important food, feed, and energy crop. Two categories of BNIs are released from maize roots; hydrophobic and hydrophilic BNIs, that determine BNI-capacity in root systems. Zeanone is a recently discovered hydrophobic compound with BNI-activity, released from maize roots. The objectives of this study were to understand/quantify the relationship between zeanone activity and hydrophobic BNI-capacity. We assessed genetic variability among 250 CIMMYT maize lines (CMLs) characterized for hydrophobic BNI-capacity and zeanone activity, towards developing genetic markers linked to this trait in maize. CMLs with high BNI-capacity and ability to release zeanone from roots were identified. GWAS was performed using 27,085 SNPs (with unique positions on the B73v.4 reference genome, and false discovery rate = 10), and phenotypic information for BNI-capacity and zeanone production from root systems. Eighteen significant markers were identified; three associated with specific BNI-activity (SBNI), four with BNI-activity per plant (BNIPP), another ten were common between SBNI and BNIPP, and one with zeanone release. Further, 30 annotated genes were associated with the significant SNPs; most of these genes are involved in pathways of "biological process", and one (AMT5) in ammonium regulation in maize roots. Although the inbred lines in this study were not developed for BNI-traits, the identification of markers associated with BNI-capacity suggests the possibility of using these genomic tools in marker-assisted selection to improve hydrophobic BNI-capacity in maize.

Figure 1

Histogram with CML mean of (a) BNI-activity per plant, (b) specific BNI-activity and (c) Zeanone intensity per plant. In all cases a clear skewed distribution is shown, with a small portion of the samples coming under highest BNI-capacity.

Figure 2

Violin plot showing SNP distribution based on physical position (bp) in each chromosome. There is a homogeneous distribution of the markers on the reference genome (B73 RefGen v.4).

Figure 3

Manhattan Plot showing significant markers associated with: (a) Specific BNI-activity (SBNI); (b) BNI-activity Per Plant (BNIPP); and (c) Zeanone intensity. The horizontal scale shows the physical position of each SNP on the reference genome B73 (RefGen v.4). Significant markers (18) are distributed across all chromosomes.

Figure 4

(A) Gene annotation for significant SNPs. (B) Top 20 reached Gene Ontology terms found by functional enrichment analysis. A total of 30 genes were mapped through 18 significant markers identified by GWAS analysis, with 48.49% positioned on transcript and upstream regions. Most of these genes are involved on the pathways of “biological process”, six of them were related to nitrogen compound metabolic processes.

Figure 5

Distribution of candidate genes identified by GWAS across maize genome (RefGen B73 v.4). In chromosome 10 is possible to see the candidate gene (Zm00001d025894/AMT5) with a very well knowing function on nitrogen transportation transmembrane. Note: tandem duplications were indicated by red font.

Figure 6

Linear simple regression of the CML mean natural logarithms of BNI per plant (BNIPP) with Zeanone intensity. R²: Coefficient of determination (%). The relationship between ln Zeanone and ln BNIPP when only 50 CMLs (red, batch 2) are included in the analysis is higher than when are used all 250 CMLs (blue + red, batch 1 and batch 2). Correlation between Zeanone intensity and BNIPP was larger for quality protein maize lines (r = 0.62, filled circle) than non-QPM lines (r = 0.23, empty triangle), CML without QPM information are represented with empty squares.