predicted proteins encoded by ZmARF genes varied from 418 amino acids
(ARF13) to 1147 amino acids (ARF20), with corresponding molecular weights from 46.84  kDa (ARF13) to 127.24 (ARF20) kDa, and the theoretical isoelectric
points ranging from 5.38 (ARF33) to 9.27 (ARF13).  The phylogenetic tree
of all maize ARF nucleotide sequences was generated using MAGE v7.0 program by
the N–J method.  All ZmARFs were
classified into 3 major classes—I, II, and III 
(Figure. 1).  Class I and II contained 22
and 2 members, respectively.  Class III
contained 13 members.  These
results are similar to the grouping of these genes in  related studies (Kumar et al.,2011;Li et

Maize ARF nucleotide sequences were downloaded from (  Alignment of
the sequences of the ARF genes was performed using CLUSTALW program in
MEGA software version 6 (Tamura et al., 2013).  Phylogenetic tree  was constructed using the the
neighbour-joining (NJ) method and diagrams of phylogenetic trees were drawn
with MEGA7 ( (Tamura et al. 2013).  Also, verification and test of the phylogeny  were performed using the bootstrap method
with 1000 replicates.


of amino acid composition in ARF genes in maize and conserved motifs

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The zea mays ARF protein sequences were
downloaded from  Amino acid composition (AAC) of the ARF protein
sequences was calculated using the ProtParam tool at ExPASy website ExPASy server
( was employed to predict the theoretical isoelectric point (pI)
and the molecular weight (Mw) of each ZmARF protein.  ZmARF transcription factors were
identified using MEME (Suite version 4.9.1; according to the following criteria: maximum number of 15 motifs
and an optimum width of 8-50 amino acids.


ZmARFs on maize chromosomes and cis-regulatory elements analysis

total of 38 ARF genes were mapped to chromosomes 1–11.  In order to show
chromosomal locations of zea mays ARF genes, the MapChart software
version 2.3 (Voorrips 2002) was downloaded from Genes promoter analysis for each gene was used
from database PlantCARE  (Lescot et
al.,2002) ( webtools/plantcare/html/) for prediction of cis regulatory

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