







































Highlights in Bioscience;


 
Highlights in BioScience             

ISSN: 2682-4043 

DOI:10.36462/H.BioSci.20194                                                                                                          
 

 
Highlights in BioScience                                                                                                                                                               November 2019 | Volume 2 

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Research Article 

 

Open Access 

 
 

 

 

 

 

1 MGGM lab., Agricultural Genetic Engineering 

ResearchInstitute, Agricultural  Research 

Center, Egypt.  
2 Genetics Department, Faculty of Agriculture, 

Mansoura University. 
3 Faculty of Pharmacy, October 6 University, 

Giza, Egypt.  
4 Department of Biodiversity and Crop 

Improvement, International Center for  
   Agriculture Research in the Dry Areas 

(ICARDA), Giza, Egypt. 

 
* To whom correspondence should be 

addressed: smahmoud@ageri.sci.eg 
 

Citation: Alsamman A.M, Mousa K.H., Nassar 

A.E.,  Shereif G.A.,  Habib P.T. and  Ibrahim 

S.D. (2019). Genome-wide identification and 

comprehensive study of chickpea anti-fungal 

genes. Highlights in BioScience, Volume 2. 

Article ID 20194, dio:10.36462/ 

H.BioSci.20194 

 

 

 
Received: September 15, 2019 

 

Accepted: October 20, 2019 

 

Published: November 10, 2019 

 

 
Copyright: © 2019 Alsamman et al. This is an 

open access article distributed under the terms 

of the Creative Commons Attribution License, 

which permits unrestricted use, distribution, 

and reproduction in any medium, provided the 

original author and source are credited. 

 

 
Data Availability Statement: All relevant data 

are within the paper and supplementary 

materials 

 

Funding: The authors have no support or 

funding to report. 

 

Competing interests: The authors declare that 

they have no competing interests 

Genome-wide identification and comprehensive 

study of anti-fungal genes in chickpea 

Alsamman M. Alsamman *
1
 , Khaled H. Mousa 

2
, Ahmed E. Nassar 

2
, Ghada 

A. Shereif 
3
, Peter T. Habib 

4
 and Shafik D. Ibrahim 

1
 

 

 

Abstract 

Chickpea is an important crop that delivers nutritious food to the 

increasing global community and it will become increasingly popular as a 

result of climate change. Our objective was to use comprehensive data 

analysis to locate and identify candidate genes for fungal disease 

resistance. We used a comprehensive bioinformatics pipeline of sequence 

alignment, phylogenetic analysis, protein chemical and physical properties 

assessment and domain structure classification. In order to study gene 

evolution and genetic diversity, we compared these genes with known 

anti-fungal genes in different species of plants. A total of 19721 protein 

sequences belonging to 187 plant species have been downloaded from 

public databases, including the entire chickpea genome. We have 

successfully identified 23 potential anti-fungal genes in 10 different 

chromosomes and genomic scaffolds using sequence alignment and gene 

annotation. Ca2 and Ca6 have the highest number of genes followed by 

Ca3 and Ca4. Anti-fungal chickpea proteins have been identified as 

cysteine-rich (10), thaumatin (6), pathogenesis (4) and plasmodesmata (3) 

proteins. Analysis of the chemical and physical correlation of anti-fungal 

proteins revealed a high correlation between different aspects of 

anti-fungal proteins. Five different pattern patterns have been detected in 

the anti-fungal chickpea proteins identified, including domain families 

associated with fungal resistance. The maximum likelihood of 

phylogenetic analysis was successful in distinguishing between 

anti-fungal chickpea proteins as seen in their protein patterns / domains.  

 

Keywords: Chickpea, Fungal resistance, Phylogenetic analysis, Protein domain, 

Protein property.  

 

Introduction  

Chickpea (Cicer arietinum) is an important crop that delivers nutritious food 

to the increasing global community and it will become increasingly popular as a 

result of climate change. Production ranked third following beans with an average 

annual yield of over 11.5 million tons, where India has the highest share. Land 

allocated to chickpea has dramatically increased and is now reported at 14.56 

million hectares. More than 2.3 million tons of chickpea reach world markets every 

year to fund the requirements of countries unable to satisfy domestic consumption 

(1). 



 
 

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Chickpea yield is significantly affected by both abiotic 

as well as biotic stress susceptibility (2,3). Fungal infections 

have been shown to destructive effects on the chickpea 

production compared to various diseases triggered by a 

wide range of pathogens. Within numerous fungal diseases, 

the most prevalent foliar and root infections are the diseases 

caused by Ascochyta rabiei (Ascochyta blight) and 

Fusarium oxysporum (fusarium wilt), respectively, which 

cause serious crop yield decline (4).  

The genome of chickpea (2n = 2x = 16) is estimated to 

be 738.09 Mb in length, where different cultivars whole 

genomes have been introduced for publicly use with more 

than 73% of the genomic content has been successfully 

sequenced. The chickpea gene pool is estimated to be about 

29,000 genes, and about half (49.41%) of the chickpea 

genome consists of transposable elements and unclassified 

repetitions. On the other hand, in species-specific groups, 

4,468 chickpea genes occur, these groups may arise through 

structural rearrangements, as happens among the disease 

resistance genes of nucleotide-binding site leucine-rich 

repeat (NBS-LRR). In this regard, it has been stated that the 

chickpea genome has been observed as having 187 disease 

resistance gene homologs (RGHs) (5,6). 

The continuing breakthroughs in genome sequencing 

and genome-wide association studies have unlocked the 

ability to scan genomic content of chickpea for genes to 

control their resistance to multiple infections of the fungal 

disease. Several predicted genes have been reported to have 

been statistically associated with chickpea fungal 

resistance, including NBS-LRR receptor-like kinase, 

wall-associated kinase, zinc finger protein, and serine / 

threonine protein kinase  (7). In addition, it has been 

reported that chickpea resistance to some fungal diseases, 

such as Ascochyta blight, may be linked to a number of 

motif families, such as AT-hook motif containing nuclear 

localized (AHL) (8). In addition, bioinformatics methods 

have been accelerated over the last few years and several 

genomic and molecular databases have been established 

(9). Such repositories could be used as a central stone in the 

quest for anti-fungal resistance in different plant species 

and in the analysis of their specific and special molecular 

structure (10,11). Such bioinformatics tools have been used 

to study several gene families in chickpea, these families are 

considerably important in the plant defense system and 

essential membrane proteins (12,13). 

Genome-wide characterization of anti-fungal genes in 

chickpea may enable researchers and breeders to overcome 

different fungal infections and develop new cultivars with 

high tolerance and better yield. Our objective was to use 

comprehensive data analysis to locate and identify 

candidate genes for fungal disease resistance. We used a 

comprehensive bioinformatics pipeline of sequence 

alignment, phylogenetic analysis, protein chemical and 

physical properties assessment and domain structure 

classification. In order to study gene evolution and genetic 

diversity, we compared these genes with known anti-fungal 

genes in different species of plants. 

Materials and Methods 

Genomic sequences related to anti-fungal resistance 

have been downloaded from the NCBI database. (14). A 

total of 19721 sequences of proteins belonging to 187 

species of plants were downloaded from NCBI. The 

chickpea genome sequence was downloaded from the 

http:/www.cicer.info database (5). Using the chickpea 

genome, the local BLAST+ (15) kit was used to create 

sequence database and align all anti-fungal amino acids 

with TBLASTN against the chickpea database. The NCBI 

TBLASTN online tool was used to annotate recovered 

sequences from the previous step. MEME suite (16) was 

used to explore patterns of amino acids in chickpea 

anti-fungal genes. The MegaX program was used to 

perform a phylogenetic analysis using a maximum 

likelihood algorithm(17). In order to assess the chemical 

and physical characteristics of the amino acids, the Pepstat 

program (18) was used through in-home perl scripts. These 

chemical properties are, A280 Molar Extinction 

Coefficients cystine bridges (A280-MECcb), A280 Molar 

Extinction Coefficients reduced (A280-MECr), Acidic 

(Ac), Aliphatic (Aph), Aromatic(Ar), Average Residue 

Weight (ARW), Basic (Bs), Charge (Chr), Charged (Chrd), 

Improbability of expression in inclusion bodies (IEEB), 

Isoelectric Point (IP), Molecular weight (MW), Non-polar 

(NP), Polar (Po), Residues (Re), Small (S), Tiny (T). The 

iTOL online tool was used to visualize phylogenetic trees 

combined with information on amino acids (19)⁠ . The 

statistical correlation analysis (pvalue<0.01) was conducted 

using R packages (20). The Circos package was used for 

displaying the genomic location of genes (21). 

Results and Discussion 

Identification of chickpea anti-fungal genes 

Identifying anti-fungal genes in chickpea could 

provide a useful resource for plant breeding programs by 

narrowing the pool of targeted genes. We have successfully 

identified 23 potential anti-fungal genes on 10 different 

chromosomes and genomic scaffolds (File S1). The total 

number of amino acids was 7077, ranging from 147 to 866, 

with an average of 307.7 amino acids. Chromosomes Ca2 

and Ca6 have the highest number of genes (4 genes) 

followed by Ca3 and Ca4 (3 genes) (Figure 1 and Table 

1). In this regard, the entire genome re-sequencing of 

chickpea was used to identify 12 chromosomal regions 

associated with resistance to Ascochyta Blight, all of which 



 
 

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are located on Ca4 (7). In addition, 8 quantitative trait loci 

(QTLs) were identified on chromosomes Ca2, Ca3, Ca4, 

Ca5 and Ca6 for the resistance of the same disease (22). 

 

The chemical and physical properties of chickpea 

anti-fungal proteins 

The chemical properties of the chickpea anti-fungal 

proteins were assessed across 17 different chemical and 

physical features of the amino acids. The total amino 

acid MW was 765.4, ranging from 16.0 KDa (Ca AF17) 

to 97.7 KDa (Ca AF9) with an average of 33.3 KDa 

(Figure 2 and Table 2). By studying anti-fungal 

proteins in wheat total MW 1913 KDa with an average 

of 20 KDa (10). The amino acids charge ranges from -25 

to (Ca_AF13) to 14 (Ca_AF9) (Figure 2 and Table 

2).The extinction coefficient is a measure of how much 

light at a given wavelength a chemical element 

attenuates. Calculating the content of the amino acid is 

necessary in order to determine the protein's molar 

extinction coefficient (23).  

The A280 Molar Extinction Coefficients reduced 

(A280-MECr) and A280 molar extinction coefficients 

cystine bridges (A280-MECcb) are two separate 

extinction coefficient measures, where salt bridges are 

essential motifs of the tertiary protein structure and are 

mostly associated with the molecular influence force that 

maintains the protein's stability (24). The A280-MECr 

and A280-MECcb total values are 836030, 864530 

M-1cm-1, ranging from 10430 and 11555 M-1cm-1 (Ca 

AF11) to 87560 and 90560 M-1cm-1 (Ca AF9), 

respectively (Figure 2 and Table 2). In some 

anti-fungal wheat proteins, the A280-MECc and 

A280-MECr minimum scores were recorded as 1740 

and 1490, with the highest scores being 104570 and 

103820 respectively (10). Improbability of expression in 

inclusion bodies (IEEB) is a type of solubility 

measurement. In Escherichia coli, for example, 

recombinant protein can be produced either as insoluble 

in the bodies of inclusion or soluble throughout the 

cytosol (25). The total IEEB of chickpea anti-fungal 

protein was 18.33 ranging from 0 (Ca_AF11) to 0.972 

(Ca_AF16) with a mean of 0.797 (Figure 2 and Table 

2). The IEIB of anti-fungal amino acids revealed an 

average of 0.794 by examining wheat anti-fungal 

proteins, ranging from 0.504 to 0.977 (10). The average 

collective weight as per their length for all amino acid 

sequences is measure though The average residue 

weight (ARW).

 

Table 1: The chromosomal location and gene definition for identified anti-fungal genes in chickpea genome. 

Gene code Chr. start end gene name Gene code Chr. start end gene name 

Ca_AF1 Chr1 13449810 13450553 cysteine-rich Ca_AF13 Chr5 15134097 15134777 pathogenesis-related 

Ca_AF2 Chr1 39499412 39500080 thaumatin Ca_AF14 Chr5 64978467 64979294 cysteine-rich 

Ca_AF3 Chr2 15365865 15366560 plasmodesmata-located Ca_AF15 Chr6 11037122 11037844 pathogenesis-related 

Ca_AF4 Chr2 15365877 15366521 plasmodesmata-located Ca_AF16 Chr6 12421759 12422469 thaumatin 

Ca_AF5 Chr2 22066674 22068239 cysteine-rich Ca_AF17 Chr6 13070688 13071419 cysteine-rich 

Ca_AF6 Chr2 29604091 29604798 thaumatin Ca_AF18 Chr6 65201755 65202474 plasmodesmata-located 

Ca_AF7 Chr3 39833663 39834379 cysteine-rich Ca_AF19 Chr7 24258666 24259331 thaumatin 

Ca_AF8 Chr3 51987009 51987668 cysteine-rich Ca_AF20 Chr8 18540320 18541342 cysteine-rich 

Ca_AF9 Chr3 59460263 59461033 cysteine-rich Ca_AF21 Chr8 5747704 5748729 thaumatin 

Ca_AF10 Chr4 2480078 2480725 cysteine-rich Ca_AF22 Scaffold0585 6485 7156 thaumatin 

Ca_AF11 Chr4 4601812 4602510 cysteine-rich Ca_AF23 Scaffold4365 250412 251062 pathogenesis-related 

Ca_AF12 Chr4 56994913 56995608 pathogenesis-related      

 



 
 

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Figure 1 : The genomic location and suggested definition of predicated anti-fungal genes, where the width of the internal links 

indicates similarity percentage of gene sequences. 

 

  The total ARW was 2478.4 Da, where Ca AF13 and 

Ca AF14 have the minimum and maximum values of 

101.8 Da and 116.7 Da, with an average of 107.7 Da, 

respectively. The IEIB of anti-fungal amino acids revealed 

an average of 0.794, ranging from 0.504 to 0.977, through 

examining wheat anti-fungal proteins (10). The isoelectric 

point (IP) is the pH level with which the net charge of the 

protein is positive, and is correlated with amino acid 

composition and protein structure (26). The IP of chickpea 

anti-fungal proteins range from 3.9 (Ca_AF13) to 8.9 

(Ca_AF19) with a mean of 6 (Figure 2 and Table 2). 

Thus, it revealed a collective IP in wheat anti-fungal 

proteins with an average of 6,402, ranging from 4 to 10.4 

in wheat (10). 

  In addition, the folded structure of a protein becomes 

less desirable in terms of thermodynamics because it 

decreases the protein disorder or entropy, where non-polar 

chains tend to squeeze inside the protein while polar 

chains push outside the molecule (27). The non-polar (NP) 

values ranges from 49.2 (Ca_AF20)  to 62.1 (Ca_AF16) 

with an average of 56 (Figure 2 and Table 2). The 

non-polar and polar amino acid scores ranged from 48.81 

and 30.081 to 69.919 and 51.19 respectively, in wheat 

anti-fungal proteins (10). Basic amino acids have a certain 

basic group within the chain whereas acidic amino acids 

have an acidic group within the chain. basic amino acids 

have high pKa while acidic amino acids have low pKa. 

The count of basic and acidic amino acids range from 

9.011 and 9.359 to (Ca_AF13 and Ca_AF16) to 13.613 

and 16.915 (Ca_AF19  and Ca_AF11) (Figure 2 and 

Table 2). 

 



 
 

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Figure 2: The chemical and physical properties of identified anti-fungal proteins in chickpea. 

 



 
 

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Table 2: Chemical properties of identified anti-fungal proteins in chickpea. 

protein  A280-MECcb A280-MECr Ac Aph Ar ARW Bs Chr Chrd IEEB IP MW NP Po Re S T 

Ca_AF1  54470 52720 11.364 24.621 10.606 109.947 11.364 -2 22.727 0.82 5.8518 58051.77 51.894 48.106 528 55.303 33.712 

Ca_AF2  29420 28420 7.207 21.622 10.811 104.536 8.108 2 15.315 0.951 7.5063 23206.95 56.306 43.694 222 69.369 47.748 

Ca_AF3  40365 38740 10 26 9 105.494 8 -8 18 0.77 4.5636 42197.5 60.5 39.5 400 63 42.5 

Ca_AF4  20120 19370 9.953 25.118 9.479 104.952 9.005 -3 18.957 0.787 4.929 22144.77 58.768 41.232 211 63.981 44.076 

Ca_AF5  59135 57760 8.802 22.005 13.447 113.33 10.024 2 18.826 0.845 6.899 46352.15 49.633 50.367 409 54.279 32.763 

Ca_AF6  40295 39420 7.623 24.215 11.659 109.223 9.417 3.5 17.04 0.949 7.7696 24356.69 57.399 42.601 223 61.435 34.978 

Ca_AF7  12545 11920 10.596 25.166 8.609 106.551 10.596 0 21.192 0.818 6.208 16089.2 56.954 43.046 151 58.278 38.411 

Ca_AF8  31830 30830 10.638 26.596 11.702 108.504 9.574 -5.5 20.213 0.74 4.941 30598.04 53.191 46.809 282 57.092 39.362 

Ca_AF9  90560 87560 10.162 26.328 12.009 112.861 12.009 14 22.171 0.793 7.9722 97737.52 53.118 46.882 866 51.27 30.947 

Ca_AF10  34155 32780 8.122 22.843 12.183 107.791 8.629 0 16.751 0.841 6.4334 42469.67 54.315 45.685 394 58.376 41.117 

Ca_AF11  11555 10430 16.915 22.886 10.448 113.048 8.955 -17 25.871 0 4.082 22722.56 49.751 50.249 201 51.244 32.338 

Ca_AF12  36410 35410 8.072 23.767 11.211 102.971 6.726 -4 14.798 0.843 4.6572 22962.57 61.883 38.117 223 70.404 48.879 

Ca_AF13  58965 56840 9.545 20.455 10.909 101.798 4.545 -25 14.091 0.756 3.9557 44790.92 59.091 40.909 440 71.818 50.909 

Ca_AF14  40545 39420 9.17 21.834 13.1 116.75 12.227 6 21.397 0.817 7.9878 26735.85 53.712 46.288 229 48.908 27.074 

Ca_AF15  32400 31400 10 20.476 10.952 103.8 4.762 -11 14.762 0.7 3.9687 21797.95 59.048 40.952 210 69.048 51.905 

Ca_AF16  33890 32890 5.023 23.288 12.785 106.665 10.502 10.5 15.525 0.972 8.4799 23359.67 62.1 37.9 219 63.927 41.553 

Ca_AF17  18045 17420 10.884 25.17 10.204 108.53 9.524 -2 20.408 0.613 4.8281 15953.84 52.381 47.619 147 59.864 42.857 

Ca_AF18  43345 41720 9.596 27.273 10.606 106.838 8.586 -4 18.182 0.814 4.8941 42307.82 60.606 39.394 396 62.121 39.899 

Ca_AF19  23210 22460 7.33 19.895 9.424 107.128 13.613 11.5 20.942 0.949 8.9491 20461.39 58.115 41.885 191 61.78 39.267 

Ca_AF20  29630 28880 8.333 25.794 9.524 111.225 9.127 1.5 17.46 0.856 7.2867 28028.72 49.206 50.794 252 58.333 34.524 

Ca_AF21  32400 31400 7.895 20.175 11.842 104.278 6.14 -4 14.035 0.927 4.542 23775.41 57.895 42.105 228 67.982 49.561 

Ca_AF22  61820 59820 9.417 18.834 10.762 105.318 6.726 -13 16.143 0.844 4.3753 46971.95 55.605 44.395 446 68.61 43.498 

Ca_AF23  29420 28420 8.612 20.096 11.962 106.915 9.091 1 17.703 0.925 7.1537 22345.18 57.416 42.584 209 65.55 42.584 



 
 

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On the other hand, in addition to the chickpea genes 

retrieved through this study, we have studied the 

chemical and physical properties of 1216 anti-fungal 

proteins identified in different plant species (Figure 3 

and Table S2). The protein MW range from 21 KDa 

(Silene latifolia) to 97.7 KDa (Cicer arietinum) while 

the protein charge range from -25 (Cicer arietinum) to 

21 (Rosa chinensis) (Figure 3 and Table S2).  

 

 

 

The minimum ARW was 99.74 KDa (Striga 

asiatica) and the maximum 116.75 KDa (Cicer 

arietinum) (Figure 3 and Table S2). The A280-MECr 

and A280-MECcb range from 30193 and 31133 to 

87560 and 90560 M-1cm-1, respectively (Figure 3 and 

Table S2). The charged amino acids range from 8.108 

(Cephalotus follicularis) to 26.941 (Populus 

trichocarpa) (Figure 3 and Table S2). 

 

 

 

 

Figure 3 : The phylogenetic tree developed using multiple sequence alignment of chickpea anti-fungal proteins and other species, 

where its chemical and physical properties are plotted. 



 
 

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Figure 4 :Statistical correlation between different chemical and physical properties of anti-fungal proteins; (A) the heatmap of 

inter-correlation matrix and (B) the correlation networks, where pvalue > 0.01 and R
2 
> 0.3. 

 

Phylogenetic analysis and domain identification of 

anti-fungal proteins 

The phylogenetic tree constructed using 1216 

anti-fungal proteins of 187 was clustered into 11 clusters 

(Figure 3). The anti-fungal chickpea proteins identified are 

cysteine-rich (10), thaumatin (6), pathogenesis-related (4) 

and plasmodesmata (3) proteins (Figure 3).  

A protein sequence motif is a brief pattern that is 

preserved by nature. For proteins, a motif may relate to the 

active site of an enzyme or to a functional unit required to 

properly fold proteins. Hence, sequence motifs are among the 

basic functional components of molecular evolution (16). 

Five specific motifs for amino acids were discovered among 

the sequences of identified anti-fungal proteins of chickpea 



 
 

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(Figure 5). The maximum likelihood phylogenetic analysis 

was successful in distinguishing between anti-fungal 

chickpea proteins as illustrated by their protein motifs / 

domains. These motifs are motif1 (ELME000385), motif2 

(ELME000094), motif3 (ELME000321), motif4 

(ELME000003), and motif5 (ELME000287) (Figure 5). 

Motif1 is very similar to ELME000385 (pvalue of 1.60e-03), 

which functions as Mtr4-Air2-interaction site. This domain 

distinguishes the TRAMP complex, which engages in the 

nucleus with exosome-mediated degradation of abnormal 

RNAse. Oligo-adenylated tails are introduced to substrates of 

abnormal RNA by Air2 and Mtr4 , thus highlighting them for 

degradation (28). Motif2 has a high significance similarity 

with Integrin binding sites (ELME000094) with a pvalue of 

1.16e-05. Integrins are cell surface receptors which are 

responsible for cell migration, cell adhesion to extracellular 

matrix, and cell adhesion to cells (29)⁠. Motif3 is similar to 

caspase cleavage motif (ELME000321) with a pvalue of 

5.46e-03. Proteases caspases-3 and-7 play a major role in 

programmed cell apoptosis, and non-apoptotic caspases 

include involvement in immune response (30). Similarly, 

pattern 5 is similar to IAP-binding pattern (IBM): 

(ELME000287) that distinguishes Apoptosis Protein 

Inhibitor (IAP) which exhibits several immune functions, 

mitosis regulation, TNF-receptor signal transduction, and 

many more (31)⁠. Finally, motif4 was in high similar to WW 

domain ligands (ELME000003) motif, which are small but 

widespread domains are found in various regulatory 

circumstances (16). 

The maximum likelihood of phylogenetic analysis was 

successful in distinguishing between anti-fungal chickpea 

proteins as seen in their protein patterns/domains. Where it 

cluster chickpea genes into 4 clusters (Figure 6).

 

Figure 5: The domains/motifs found by the MeMe tool in chickpea predicated anti-fungal proteins. 

 

 

 



 
 

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Figure 6: The phylogenetic analysis of chickpea anti-fungal proteins, where the protein motif structures are shown as detected 

using MeMe tool.

Conclusion 
It was very helpful to predict anti-fungal resistance 

genes using publicly available repositories and indicated that 

several chickpea genes could be used to limit genetic research 

of genes that hold the key to fungal resistance in chickpea. We 

have successfully identified 23 potential anti-fungal genes on 

10 different chromosomes and genomic scaffolds. A high 

number of anti-fungal chickpea proteins are cysteine-rich 

(20), thaumatin (9), and pathogenesis-related (8), which 

could indicate the importance of these gene classes in 

chickpea resistance to fungal. In addition, the chemical and 

physical analysis shed light on the uniqueness and 

consistency of these proteins, where several of these 

parameters could be used in future research to identify 

anti-fungal genes in different plant species. Moreover, the 

domain identification analysis identified several potential 

anti-fungal protein domains such as TRAMP complex and 

caspase cleavage motifs. 

 

Supplementary Files 
 

The Supplementary Material for this article can be found 

online at: https://doi.org/10.36462/H.BioSci.20194   

Supplementary file 1: The amino acid sequences of 

anti-fungal genes identified in chickpea. 

Supplementary file 2: The physical and chemical properties 

of some anti-fungal proteins in plant species. 

 

 

 

 

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https://doi.org/10.36462/H.BioSci.20194


 
 

Alsamman et al., 2019                                                                                           Comprehensive study of chickpea anti-fungal genes 

 

 
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