Genome-wide Estimation of Evolutionary Distance and Phylogenetic Analysis of Homologous Genes

Abstract

Homologous genes, including paralogs and orthologs, are genes that share sequence homologies within or between different species. Homologous genes originate from a common origin through speciation, genetic duplication or horizontal gene transfer. Estimation of the sequence divergence of homologous genes help us to understand divergence time, which makes it possible to understand the evolutionary patterns of speciation, gene duplication and gene transfer events. This protocol will provide a detailed bioinformatics pipeline on how to identify the homologous genes, compare their sequence divergence and phylogenetic relationships, focusing on homologous genes that show syntenic relationships using soybean (Glycine max) and common bean (Phaseolus vulgaris) as example species.

Background

Gene duplication, including whole genome duplication or polyploidy, segmental duplication, and tandem duplication, is a very important process that increases gene copy number and thus enhances genetic diversity in many organisms. Because of this, gene duplication is thought to be a major force in evolution (Ohno, 1970; Otto and Whitton, 2000; Blanc and Wolfe, 2004; Jiao et al., 2011 ). After duplication, duplicated genes are subject to a variety of changes, such as accumulation of point mutations, insertions and deletions, gene conversion and transposon insertions ( Ilic et al., 2003 ; Gu et al., 2005 ; Sémon and Wolfe, 2007). Theoretically, two or multiple copies of the duplicated genes have undergone different levels of selective constraint, which makes the functional divergence of the duplicated genes. This can be reflected on the sequence divergence of the homologous genes, such as non-synonymous substitution (Ka) and synonymous substitution (Ks), the latter of which the produced amino acid sequence is not modified. Because it is neutral with respect to selection, Ks can be used to determine rough divergence time. The ratio of Ka/Ks can be used to estimate the selection pressure on genes. A Ka/Ks ratio equal to one indicates a lack of selection, as is observed in pseudogenes. The ratio of Ka/Ks higher and lower than one implies positive and purifying selection, respectively. The values of Ka/Ks for the vast majority of genes are < 1.0 due to purifying selection to maintain function (Makalowski and Boguski, 1998; Nekrutenko et al., 2002 ). When comparing duplicate genes, differences in Ka/Ks suggest different levels or kinds of selection.

In order to determine the evolutionary distance, we first need to identify the homologous genes within or between different species. Here, we will mainly focus on the homologous genes that show syntenic relationships between different species. Syntenic genes are those genes that retain an ancestral position on a given region of a chromosome. We refer to these syntenic homologous genes as “syntelogs” ( Zhao et al., 2017 ). The advantage of focusing on syntelogs is that if they are the result of polyploidy, all syntelogs arose at the same time, so groups of syntenic gene pairs can be compared with high confidence. Here, we describe a detailed pipeline for the identification and comparison of the evolutionary distance of syntelogs by using soybean (Glycine max) and common bean (Phaseolus vulgaris) as example species (Figure 1). It has been proposed that soybean has experienced a recent whole genome duplication event roughly 5 to 13 million years ago (MYA, Schmutz et al., 2010 ), occurring after the split with its close relative common bean roughly 19 MYA ( Lavin et al., 2005 ; McClean et al., 2010 ). In this protocol, we will estimate the evolutionary divergence of the duplicated gene pairs in soybean by comparing them with the orthologous genes in the common bean genome.

Figure 1. Bioinformatics pipeline for identification and comparison of the syntenic homologous genes in soybean and common bean.

The solid and the dotted circles indicate the presence and absence of the genes in the corresponding genomes, respectively. GmA and GmB represent either of the duplicated genes in soybean. Gm, Glycine max, soybean; Pv, Phaseolus vulgaris, common bean. This figure was modified from Zhao et al., 2017 .

Equipment

1. Linux/Unix cluster

   In this study, we use the Purdue Halstead supercomputer, which contains 508 nodes in total. Each node contains 20 cores, two 10-Core Intel Xeon-E5 processors, and 128 GB memory. Please refer to the website for more information: https://www.rcac.purdue.edu/compute/halstead.

2. Personal computer for post data processing (Lenovo, T430s, Intel Core i5-3320M CPU, 4 GB RAM)

Software

1. Blastall or Blast+ ( Altschul et al., 1997 )

   https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastDocs&DOC_TYPE=Download

   This program is developed and distributed by NCBI to do blast searches.

2. MCScanX ( Wang et al., 2012 ), http://chibba.pgml.uga.edu/mcscan2/

   This toolkit is for detection and evolutionary analysis of gene synteny and collinearity. This program also can generate tandemly duplicated genes.

3. Multiple Sequence Comparison by Log-Expectation (MUSCLE) (Edgar, 2004), https://www.drive5.com/muscle/

4. ClustalW ( Thompson et al., 1994 ), http://www.clustal.org/clustal2/

   Both Muscle and ClustalW are software for multiple sequence alignment for nucleotide and protein sequences.

5. Phylogenetic Analysis by Maximum Likelihood (PAML) ( Yang et al., 2007 ), http://abacus.gene.ucl.ac.uk/software/paml.html

   PAML is a package of programs for phylogenetic analyses of DNA or protein sequences using maximum likelihood.

6. Molecular Evolutionary Genetics Analysis (MEGA X) ( Kumar et al., 2018 ), https://www.megasoftware.net/

   This software contains many sophisticated methods and tools for phylogenetic analysis, including constructing phylogenetic trees as well as evolutionary distance estimation.

7. Perl, https://www.perl.org/, or Python, https://www.python.org/, programming languages

   These languages make it possible to post-process the primary data generated from some of the software used above.

8. SAS software, https://www.sas.com/en_us/home.html

   SAS is a software for statistical analysis.

Procedure

1. Identification of Syntenic Genes among Closely Related Species

   1. Retrieve gene sequence

      For given plant genomes of which the genome annotation is available, download the coding sequences (CDS) and protein sequences of all the protein-encoding genes from corresponding databases. Some species have their respective websites, such as Arabidopsis TAIR (https://www.arabidopsis.org/), soybean SoyBase (https://soybase.org/), and maize MaizeGDB (https://www.maizegdb.org/), etc. The sequences of many of other species were deposited at NCBI (https://www.ncbi.nlm.nih.gov/), CoGe (https://genomevolution.org/coge/), Phytozome (https://phytozome.jgi.doe.gov/pz/portal.html) or other relevant databases. We downloaded all the genome sequences and gene annotation of soybean (v1.1, Schmutz et al., 2010 ) and common bean ( Schmutz et al., 2014 ) from Phytozome.

   2. Removal of transposon-related and hypothetical proteins

      In order to detect highly confident syntelogs among closely related species, transposon-related and hypothetical proteins were first removed using BLAST ( Altschul et al., 1997 ). Taking soybean (v1.1) as an example, in total 53,927 annotated genes from the 20 soybean chromosomes were BLASTN queried against the soybean transposon database SoyTEdb ( Du et al., 2010 , https://www.soybase.org/soytedb/). Any genes over the 80% of the total length matching the transposon-related sequences with the sequence similarities of greater than 80% were removed. Genes annotated as hypothetical proteins were excluded as well (Figure 1). Here is a typical setting for doing local blast.

      formatdb -i SoyBase_TE_Fasta.txt -p F -o T

      blastall -p blastn -i Soybean_gene_cds.fa -d SoyBase_TE_Fasta.txt -m 8 -a 8 -o Soybean_gene_cds_blast_TEs

      Note: Hypothetical proteins were identified based on the gene annotation file. The genes annotated as hypothetical proteins were not included in the analysis. Here formatdb is to format the nucleotide source database “SoyBase_TE_Fasta.txt” before it can be searched using blastall. blastall is used to compare the gene sequences in the file “Soybean_gene_cds.fa” with the database “SoyBase_TE_Fasta.txt”. A detailed description of each parameter can be found in the software manual.

   3. Detection of candidate syntelogs

      The remaining protein-encoding genes in soybean and common bean were used to do an all-against-all BLASTP search using default parameters, with the E-value cutoff 10^-10 ( Altschul et al., 1997 ). For each pair of genes, BLAST hits were loaded to the software MCScanX ( Wang et al., 2012 ) to scan the syntelog homologous gene pairs.

      blastall -p blastp -i Soybean_gene_pep.fa -d Commonbean_gene_pep.fa -m 8 -a 8 -F F -o Soybean _blast_Commonbean

      MCScanX Soybean_CommonBean

      Note: The setting of E-value is based on the rough divergence time. You can leave it as default setting if the divergence time is unknown. Please prepare the required gff file for all gene locations to MCScanX. Syntenic gene pairs between soybean and common bean were identified with MCScanX’s default settings (Match Score = 50, Match Size = 5, Gap Penalty = -1, Overlap Window = 5, Max Gaps = 25 and an E-value cutoff 10^-10).

   4. Post process the candidate syntelogous genes

      Since soybean has undergone a whole genome duplication after its split with common bean, the genes in the common bean genomes were corresponding to one or two copies in the soybean genome, depending on the duplication status of the genes retained in soybean. MCScanX provided all the homologous gene pairs in addition to syntelogous gene pairs. In order to remove the false positive syntelogous genes, the duplicated block information from the reference genome was incorporated ( Schmutz et al., 2014 ) to keep the homologous gene pairs detected in the duplicated regions and showing syntenic relationship between soybean and common bean.

      Example of the final list of candidate syntelogous genes was shown in Table 1. Genes involved in tandem duplication have an ambiguous retention status and thus were put aside for separate analysis.

      ||Gene is not detected in the syntenic regions.

2. Estimation of Evolutionary Distance for Syntelogous Genes

   1. Sequence alignment

      Although many genes have several alternative transcripts, only the primary transcripts of the genes based on the gene annotation were used to estimate the sequence divergence between different syntenic genes of soybean and common bean. The nucleotide sequences of the syntenic genes were aligned using the MUSCLE program (Edgar, 2004) or ClustalW ( Thompson et al., 1994 ) using default parameters. The alignment can be viewed by Jalview (Figure 2A).

      muscle -in input -out output or clustalw input

      Note: The primary transcripts of the genes were determined based on the gene annotation file which shows the primary transcripts of the genes. MUSCLE or ClustalW can only run one group of syntelogs at a time. For whole genome level analysis, we recommend that the authors write a Perl or Python script to automatically load each pair of sequences to MUSCLE or ClustalW to do the alignment. At this step, we used MUSCLE to run the alignment first, and then performed ClustalW for the remained gene pairs of which the nucleotide alignments were not integer multiples of three after MUSCLE alignment.

   2. Manual inspection

      The output alignment was manually inspected to modify incorrectly aligned nucleotides. This step is very important although it may not be practical if there is a very large amount of data to verify (Figure 2B).

   3. Sequence divergence

      All pairwise alignments of the syntenic genes were prepared into the required format by the PAML software using Perl or Python programming in order to calculate non-synonymous (Ka) and synonymous (Ks) substitution using the yn00 and baseml modules with the default parameters except model was set to 1 instead of 0 (Yang, 2007). Please refer to the manual for more information about running programs in the PAML package.

3. Phylogenetic analysis

   Phylogenetic trees are used to tell the phylogenetic relationship among homologous genes.

   1. Sequence Alignment

      The nucleotide sequences or protein sequences of the syntenic genes were aligned using the MUSCLE program (Edgar, 2004) or ClustalW ( Thompson et al., 1994 ) using default parameters.

      muscle -in input -out output or clustalw input

   2. Phylogenetic Tree Construction

   The sequence alignments of the homologous genes were transferred to MEGA software to construct the phylogenetic trees using the neighbor-joining maximum composite likelihood model integrated for nucleotide sequences and Poisson correction for protein sequences with pairwise deletions ( Kumar et al., 2018 ). Bootstrap values were calculated from 1,000 replicates.

Table 1. Example of syntenic homologous genes identified in the common bean and soybean genomes.

Common bean gene	Chr.	Position1	Position2	Soybean gene1	Chr.	Position1	Position2	Soybean gene2	Chr.	Position1	Position2
Phvul.001G000300	Chr01	125452	132387	Glyma14g39740	Gm14	48837023	48842461	Glyma17g38230	Gm17	41861916	41866671
Phvul.001G000400	Chr01	134609	140566	||	||	||	||	Glyma17g38220	Gm17	41850751	41859809
Phvul.001G000500	Chr01	144309	146169	Glyma14g39760	Gm14	48850989	48853387	Glyma17g38210	Gm17	41848054	41849712
Phvul.001G000600	Chr01	149887	162657	Glyma14g39783	Gm14	48860578	48876653	||	||	||	||
Phvul.001G000700	Chr01	165085	167549	Glyma14g39770	Gm14	48856134	48858026	Glyma17g38190	Gm17	41836453	41838879
Phvul.001G000800	Chr01	169087	171622	Glyma14g39790	Gm14	48884566	48887025	||	||	||	||
Phvul.001G000900	Chr01	179027	180468	||	||	||	||	Glyma17g38150	Gm17	41825405	41826909
Phvul.001G001000	Chr01	181478	184265	Glyma14g39810	Gm14	48888100	48891528	Glyma17g38140	Gm17	41819484	41822880
Phvul.001G001100	Chr01	186295	192859	Glyma14g39820	Gm14	48896234	48903798	||	||	||	||
Phvul.001G001200	Chr01	194851	202568	Glyma14g39830	Gm14	48906128	48915630	||	||	||	||
Phvul.001G001300	Chr01	204982	207864	Glyma14g39840	Gm14	48917945	48921504	||	||	||	||
Phvul.001G001400	Chr01	209557	221981	Glyma14g39850	Gm14	48926607	48941089	Glyma17g38130	Gm17	41805714	41816222
Phvul.001G001500	Chr01	234187	238304	Glyma14g39880	Gm14	48951994	48956982	Glyma17g38120	Gm17	41792749	41801329

Figure 2. An example of sequence alignments of syntenic homologous genes in soybean and common bean.

A. Original alignment generated by MUSCLE (Edgar, 2004). B. Manually modified alignment. Blue boxes indicate modified regions.

Data analysis

Student’s t-test was performed to compare the evolutionary distance between duplicates and singletons using the SAS software. The Bonferroni correction was further performed to correct the P values. P < 0.05 was considered to be significant, and P < 0.0001 was considered to be significant under the Bonferroni correction. Experimental values are reported as mean ± standard deviation or in a box plot (Figure 3).

Figure 3. Comparison of the evolutionary distance between duplicates and singletons in soybean.

Ka and Ks were calculated by pairwise comparison between soybean and common bean. The statistical analysis was conducted by Student’s t-test. **, P < 0.0001. Ka, non-synonymous substitution; Ks, synonymous substitution; ω, Ka/Ks. The bottom and top boundaries of the box are the first and third quartiles, and the bold lines within individual boxes are the medians, which are referred to as the second quartiles. The ends of the whiskers (the dotted lines) represent the minimum values and maximum values of the data.

Notes

1. Some designated singleton genes, the homologs of which were not found in the syntenic region, may belong to duplicated pairs because of potential gene transposition. The homologs of the singletons may be transposed or translocated from the original syntenic regions to elsewhere in the genome, rather than being deleted.

2. Genes involved in tandem duplication always have an ambiguous retention status, and thus were separately analyzed.

Competing interests

The authors declare that there are no conflicts of interest or competing interests.