Synteny

Genome evolution

Macro and microsynteny analyses

Outline

• Chromosome-level synteny
• Conserved microsynteny
• Rearrangement breakpoint rate
• Gene co-expression network analysis

Chromosome-level genome synteny

Lasz was utilized to conduct pairwise whole genome alignments, while the genome alignment tool was employed to filter and chain these alignments. The Lastz pipeline accommodates various parameters based on phylogenetic distance to achieve optimal alignments.

1. Running Lastz pipeline：

   perl step1_lacnem_v2.pl target.fa query.fa
   cd output/5.net

2. Filtering syntenic net with length < 500kb：

   mkdir netFilter; cd netFilter;
   sh step2_Net_filter.sh ../UCSC.target.filter.net ../../query.sizes

3. Macro-synteny plot with ideogram.R:

   Rscript ideogram.R # the inputs are from step2.

Conserved microsynteny

Synphoni was used to detect conserved microsyntenic blocks, in which we performed 4 steps:

1. Running Synphoni pipeline：

   sh Synphoni_step1/step2/step2.5/step3/step4.sh

Rearrangement breakpoint rate

AGORA was used to re-construct gene order in ancestors, and identify rearrangement breakpoints.

1. Orthology assessment. Please refer to our GAGA orthology analysis for details.

2. Running AGORA pipeline:

   python3 software/agora/src/agora-generic.py GAGA_phylogeny.nhx Orthogroups/orthologyGroups.%s.list genes/genesSTE.%s.list.bz2 -workingDir=output

3. Detecting rearrangement breakpoints and estimating the breakpoint rate:

   sh step3_breakpoints.sh; sh step4_timeNorm.sh

Gene co-expression network analysis

WGCNA was used in the gene co-expression network analysis.

1. We ran WGCNA using the Monomorium pharaonis developmental transcriptomes Qiu et al., 2022. We plotted the general expression dynamics of gene co-expression modules across developmental stages using Figure2C.R, the expression dynamics of conserved syntenic blocks using Figure2F.R, and the co-expression networks using Figure2D.R.

   Rscript WGCNA.R