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. 2018 Feb 21;8(1):3429.
doi: 10.1038/s41598-018-21738-7.

Genome-scale examination of NBS-encoding genes in blueberry

Affiliations

Genome-scale examination of NBS-encoding genes in blueberry

Jose V Die et al. Sci Rep. .

Abstract

Blueberry is an important crop worldwide. It is, however, susceptible to a variety of diseases, which can lead to losses in yield and fruit quality. Although screening studies have identified resistant germplasm for some important diseases, still little is known about the molecular basis underlying that resistance. The most predominant type of resistance (R) genes contains nucleotide binding site and leucine rich repeat (NBS-LRR) domains. The identification and characterization of such a gene family in blueberry would enhance the foundation of knowledge needed for its genetic improvement. In this study, we searched for and found a total of 106 NBS-encoding genes (including 97 NBS-LRR) in the current blueberry genome. The NBS genes were grouped into eleven distinct classes based on their domain architecture. More than 22% of the NBS genes are present in clusters. Ten genes were mapped onto seven linkage groups. Phylogenetic analysis grouped these genes into two major clusters based on their structural variation, the first cluster having toll and interleukin-1 like receptor (TIR) domains and most of the second cluster containing a coiled-coil domain. Our study provides new insight into the NBS gene family in blueberry and is an important resource for the identification of functional R-genes.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Analysis of the N-terminal domain in non-TNL sequences. (a) Amino acid position of predicted CC motif. (b) Regular expression of the 30–60 amino acids region from blueberry CNL sequences. Sequence logo representation was generated from multiple alignments with MEME software.
Figure 2
Figure 2
Comparative analysis between blueberry NBS sequences and other species. (a) Boxplot of identity distribution scores by plant RefSeq database. Blueberry NBS sequences were used as queries against the RefSeq database and the identity from the best-matching NBS protein for each blueberry sequence was recorded. Figure shows the five species with higher number of hits. (b) Species tree of some species in which homologs of NBS-LRR genes have been identified. The data were downloaded from NCBI Common Tree in the Taxonomy section (http://www.ncbi.nlm.nih.gov/taxonomy) and the tree was constructed using the R package “ape”.
Figure 3
Figure 3
Position of 10 NBS-LRR genes on the blueberry linkage groups. Linkage map of F1#10 × W85-23 diploid population. First and last marker on each linkage group (cM) are shown as references. Positions of NBS genes are shown in red color. Only linkage groups with NBS markers are shown.
Figure 4
Figure 4
Phylogenetic tree of NBS genes in the blueberry genome. The tree is based on the maximum likelihood method using MEGA software. Numbers on the branches indicate the percentage of 1000 bootstrap replicates. Gene names are intended to represent blueberry scaffolds and domain configurations. Numbers between brackets denote more than one gene per scaffold.
Figure 5
Figure 5
Distribution of CREs in the blueberry promoters data set and simulated control set. The control dataset is based on 2000 simulations, where each simulation contains n = 65 sequences, with length = 1500 bp per sequence, and an expected frequency GC = 0.37.

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