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1. A Likelihood Approach for Uncovering Selective Sweep Signatures from Haplotype Data

   https://doi.org/10.1093/molbev/msaa115  

   Harris, Alexandre M; DeGiorgio, Michael (May 2020, Molecular Biology and Evolution)

   Kim, Yuseob (Ed.)

   Abstract Selective sweeps are frequent and varied signatures in the genomes of natural populations, and detecting them is consequently important in understanding mechanisms of adaptation by natural selection. Following a selective sweep, haplotypic diversity surrounding the site under selection decreases, and this deviation from the background pattern of variation can be applied to identify sweeps. Multiple methods exist to locate selective sweeps in the genome from haplotype data, but none leverages the power of a model-based approach to make their inference. Here, we propose a likelihood ratio test statistic T to probe whole-genome polymorphism data sets for selective sweep signatures. Our framework uses a simple but powerful model of haplotype frequency spectrum distortion to find sweeps and additionally make an inference on the number of presently sweeping haplotypes in a population. We found that the T statistic is suitable for detecting both hard and soft sweeps across a variety of demographic models, selection strengths, and ages of the beneficial allele. Accordingly, we applied the T statistic to variant calls from European and sub-Saharan African human populations, yielding primarily literature-supported candidates, including LCT, RSPH3, and ZNF211 in CEU, SYT1, RGS18, and NNT in YRI, and HLA genes in both populations. We also searched for sweep signatures in Drosophila melanogaster, finding expected candidates at Ace, Uhg1, and Pimet. Finally, we provide open-source software to compute the T statistic and the inferred number of presently sweeping haplotypes from whole-genome data. 

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2. Identifying and Classifying Shared Selective Sweeps from Multilocus Data

   https://doi.org/10.1534/genetics.120.303137  

   Harris, AM; DeGiorgio, M (May 2020, Genetics)

   Positive selection causes beneficial alleles to rise to high frequency, resulting in a selective sweep of the diversity surrounding the selected sites. Accordingly, the signature of a selective sweep in an ancestral population may still remain in its descendants. Identifying signatures of selection in the ancestor that are shared among its descendants is important to contextualize the timing of a sweep, but few methods exist for this purpose. We introduce the statistic SS-H12, which can identify genomic regions under shared positive selection across populations and is based on the theory of the expected haplotype homozygosity statistic H12, which detects recent hard and soft sweeps from the presence of high-frequency haplotypes. SS-H12 is distinct from comparable statistics because it requires a minimum of only two populations, and properly identifies and differentiates between independent convergent sweeps and true ancestral sweeps, with high power and robustness to a variety of demographic models. Furthermore, we can apply SS-H12 in conjunction with the ratio of statistics we term Embedded Image and Embedded Image to further classify identified shared sweeps as hard or soft. Finally, we identified both previously reported and novel shared sweep candidates from human whole-genome sequences. Previously reported candidates include the well-characterized ancestral sweeps at LCT and SLC24A5 in Indo-Europeans, as well as GPHN worldwide. Novel candidates include an ancestral sweep at RGS18 in sub-Saharan Africans involved in regulating the platelet response and implicated in sudden cardiac death, and a convergent sweep at C2CD5 between European and East Asian populations that may explain their different insulin responses. 

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3. Genomic signatures of selection in bats surviving white‐nose syndrome

   https://doi.org/10.1111/mec.15813  

   Gignoux‐Wolfsohn, Sarah A.; Pinsky, Malin L.; Kerwin, Kathleen; Herzog, Carl; Hall, MacKenzie; Bennett, Alyssa B.; Fefferman, Nina H.; Maslo, Brooke (February 2021, Molecular Ecology)

   Abstract Rapid evolution of advantageous traits following abrupt environmental change can help populations recover from demographic decline. However, for many introduced diseases affecting longer‐lived, slower reproducing hosts, mortality is likely to outpace the acquisition of adaptive de novo mutations. Adaptive alleles must therefore be selected from standing genetic variation, a process that leaves few detectable genomic signatures. Here, we present whole genome evidence for selection in bat populations that are recovering from white‐nose syndrome (WNS). We collected samples both during and after a WNS‐induced mass mortality event in two little brown bat populations that are beginning to show signs of recovery and found signatures of soft sweeps from standing genetic variation at multiple loci throughout the genome. We identified one locus putatively under selection in a gene associated with the immune system. Multiple loci putatively under selection were located within genes previously linked to host response to WNS as well as to changes in metabolism during hibernation. Results from two additional populations suggested that loci under selection may differ somewhat among populations. Through these findings, we suggest that WNS‐induced selection may contribute to genetic resistance in this slowly reproducing species threatened with extinction. 

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4. VolcanoFinder: Genomic scans for adaptive introgression

   https://doi.org/10.1101/697987  

   Setter, D; Mousset, S; Cheng, X; Nielsen, R; DeGiorgio, M; Hermisson, J (June 2020, PLOS genetics)

   Recent research shows that introgression between closely-related species is an important source of adaptive alleles for a wide range of taxa. Typically, detection of adaptive introgression from genomic data relies on comparative analyses that require sequence data from both the recipient and the donor species. However, in many cases, the donor is unknown or the data is not currently available. Here, we introduce a genome-scan method—VolcanoFinder—to detect recent events of adaptive introgression using polymorphism data from the recipient species only. VolcanoFinder detects adaptive introgression sweeps from the pattern of excess intermediate-frequency polymorphism they produce in the flanking region of the genome, a pattern which appears as a volcano-shape in pairwise genetic diversity. Using coalescent theory, we derive analytical predictions for these patterns. Based on these results, we develop a composite-likelihood test to detect signatures of adaptive introgression relative to the genomic background. Simulation results show that VolcanoFinder has high statistical power to detect these signatures, even for older sweeps and for soft sweeps initiated by multiple migrant haplotypes. Finally, we implement VolcanoFinder to detect archaic introgression in European and sub-Saharan African human populations, and uncovered interesting candidates in both populations, such as TSHR in Europeans and TCHH-RPTN in Africans. We discuss their biological implications and provide guidelines for identifying and circumventing artifactual signals during empirical applications of VolcanoFinder. 

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5. Genomic determination of breeding systems and trans-specific evolution of HD MAT genes in suilloid fungi

   https://doi.org/10.1093/genetics/iyad069  

   Ke, Yi-Hong; Branco, Sara; Bazzicalupo, Anna L; Nguyen, Nhu H; Liao, Hui-Ling; Kennedy, Peter; Bruns, Thomas D; Kuo, Alan; LaButti, Kurt; Barry, Kerrie; et al (April 2023, GENETICS)

   Stajich, J (Ed.)

   Abstract Studying the signatures of evolution can help to understand genetic processes. Here, we demonstrate how the existence of balancing selection can be used to identify the breeding systems of fungi from genomic data. The breeding systems of fungi are controlled by self-incompatibility loci that determine mating types between potential mating partners, resulting in strong balancing selection at the loci. Within the fungal phylum Basidiomycota, two such self-incompatibility loci, namely HD MAT locus and P/R MAT locus, control mating types of gametes. Loss of function at one or both MAT loci results in different breeding systems and relaxes the MAT locus from balancing selection. By investigating the signatures of balancing selection at MAT loci, one can infer a species’ breeding system without culture-based studies. Nevertheless, the extreme sequence divergence among MAT alleles imposes challenges for retrieving full variants from both alleles when using the conventional read-mapping method. Therefore, we employed a combination of read-mapping and local de novo assembly to construct haplotypes of HD MAT alleles from genomes in suilloid fungi (genera Suillus and Rhizopogon). Genealogy and pairwise divergence of HD MAT alleles showed that the origins of mating types predate the split between these two closely related genera. High sequence divergence, trans-specific polymorphism, and the deeply diverging genealogy confirm the long-term functionality and multiallelic status of HD MAT locus in suilloid fungi. This work highlights a genomics approach to studying breeding systems regardless of the culturability of organisms based on the interplay between evolution and genetics. 

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