The influence of chromosomal inversions on genetic variation and clinal patterns in genomic data of Drosophila melanogaster
This chapter discusses how certain genetic changes in fruit flies can affect their genetic diversity and adaptation. It explains the methods used to study these changes and their implications for understanding evolution.
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- 1 While these analyses were restricted to a single population in Zambia, we will now investigate hundreds of populations in Europe and North America.
- 2 Now that we have estimated inversion frequencies in all populations based on the diagnostic marker SNPs, we can test if this hypothesis is true.
- 3 Furthermore, we will test for clinal patterns of the inversions in European and North American populations and investigate if these patterns can be explained by demography alone.
- 4 For example, in contrast to the vinegar fly D. melanogaster, which harbors inversions common in many worldwide populations, its sister taxa D. mauritiana and D. simulans are basically inversion-free.
Introduction
The reversal of synteny impedes homologous pairing in heterokaryotypic chromosomes, i.e., a chromosome pair, where one copy is inverted (INV) and the other of standard (ST) arrangement, and leads to loop structures inside the chromosomal region spanned by the inversion . These structures allowed investigating the influence of inversions on recombination patterns in the early days of genetics research, approximately 100 years ago, in the vinegar fly D. melanogaster [e.g.
Accordingly, the breakpoints of inversion polymorphisms, which can range from less than a thousand to several million base pairs in length, are often enriched for these repetitive sequences and predominantly occur in “weak” spots of the genome that are prone to breakage and that can even be shared across distantly related taxa .
However, the synaptonemal complexes, which initiate crossing over, can only form when the homologous chromatids are fully paired .
Particularly, if the p-value of the inversion is higher than the -log10-transformed threshold, we can assume that the clinal patterns cannot be explained by neutral evolution alone.
Research Question
Furthermore, we will test for clinal patterns of the inversions in European and North American populations and investigate if these patterns can be explained by demography alone. Now that we have estimated inversion frequencies in all populations based on the diagnostic marker SNPs, we can test if this hypothesis is true.
While these analyses were restricted to a single population in Zambia, we will now investigate hundreds of populations in Europe and North America.
Methodology
These effects range from (1) positional shifts of genes In this book chapter, I will present a bioinformatics analysis pipeline which allows to assess the influence of inversions on genetic variation in natural populations. The full analysis pipeline of this book chapter can be found at https://github.com/capoony/Chapter6-InvPopGenomics .
Study Design
Here and throughout this chapter, the code blocks, as shown below, are highlighted by boxes with different fonts and colors according to the coding syntax of the BASH shell scripts, which is the main scripting language used in this analysis pipeline (besides specific scripts written in Python and R).
However, I would strongly recommend to open the script main.sh, which is located in the shell/ folder and which contains the whole analysis pipeline shown here, in an integrated development environment (IDE) program such as the VScode ( https://code.visualstudio.com/ ) editor and execute the individual commands from the main.sh script bit by bit.
While such putative linked effects are indeed also interesting, their analysis is beyond the scope of this chapter.
While these clines may be the result of spatially varying selection, we cannot rule out based on this simple analysis that the observed clinal patterns are alternatively the result of the demographic history that shaped the differentiation of the investigated.
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Results & Findings
Chromosomal inversions are structural mutations that result in the reorientation of the gene order in the affected genomic region . As shown in Figure 1 , these characteristic inversion loops can even be examined under light microscopes in giant polytene chromosomes, which represent thousand-fold replicated chromatids within the nucleus that can be found, for example, in the salivary glands of many drosophilid larvae .
- Chromosomal inversions are structural mutations that result in the reorientation of the gene order in the affected genomic region .
- As shown in Figure 1 , these characteristic inversion loops can even be examined under light microscopes in giant polytene chromosomes, which represent thousand-fold replicated chromatids.
- Inversions can either be the result of erroneously mended double strand breaks or of ectopic recombination among repetitive and palindromic sequences, for instances tRNAs, ribosomal genes.
- For example, in contrast to the vinegar fly D. melanogaster, which harbors inversions common in many worldwide populations, its sister taxa D. mauritiana and D. simulans.
- The primary evolutionary effect of inversions is a strong suppression of recombination with standard arrangement chromosomes, since crossing-over in heterokaryotypes within the inverted region results in.
However, both inversions exhibit highly significant correlations with latitude in North America, which indicates that these clinal patterns cannot be explained by the demographic history of the investigated populations alone.
For example, in contrast to the vinegar fly D. melanogaster, which harbors inversions common in many worldwide populations, its sister taxa D. mauritiana and D. simulans are basically inversion-free.
Practical Applications
The prevalence of inversions that either include or exclude the centromere (pericentric vs. paracentric inversions) can vary dramatically, even among closely related taxa, which may be linked to varying numbers of TEs in different genomes. However, the suppression of recombination is not perfect and two processes may lead to rare genetic exchange -so called “gene flux” -across karyotypes .
Accordingly, inversions may strongly influence the patterns of genetic variation in the corresponding genomic region .
However, other factors, such as sequencing and mapping errors or imperfect LD of some diagnostic SNPs in certain geographic regions (see also above in the introduction to paragraph 3) may also influence the distribution of frequencies.
Preparing the bioinformatics analyses pipeline
The chapter outlines the steps to set up a bioinformatics pipeline, including installing dependencies, downloading genomic data, and executing scripts for SNP calling using FreeBayes.
Patterns of genomic variation and differentiation associated with different karyotypes in an African population from Zambia
The chapter discusses the analysis of genetic variation and differentiation in Drosophila melanogaster populations from Zambia, focusing on the effects of different karyotypes.
Frequently Asked Questions
Now that we have estimated inversion frequencies in all populations based on the diagnostic marker SNPs, we can test if this hypothesis is true. While these analyses were restricted to a single population in Zambia, we will now investigate hundreds of populations.
To keep the analysis pipeline concise, I collected all commands for the mapping pipeline in a separate shell script mapping.sh, which can be found in the shell/ folder. For these reasons, PCA is a very popular model-free method to quantify population structure.
For example, in contrast to the vinegar fly D. melanogaster, which harbors inversions common in many worldwide populations, its sister taxa D. mauritiana and D. simulans are basically inversion-free. Particularly large chromosomal inversions are considered to play an important evolutionary role given.
However, the suppression of recombination is not perfect and two processes may lead to rare genetic exchange -so called “gene flux” -across karyotypes . We therefore conclude that our initial hypothesis was correct and that the two inversions indeed have a major.
While such putative linked effects are indeed also interesting, their analysis is beyond the scope of this chapter. However, both inversions exhibit highly significant correlations with latitude in North America, which indicates that these clinal patterns cannot be explained by the demographic.
This chapter discusses how certain genetic changes in fruit flies can affect their genetic diversity and adaptation. It explains the methods used to study these changes and their implications for understanding evolution.