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1. Recurrent selection shapes the genomic landscape of differentiation between a pair of host‐specialized haplodiploids that diverged with gene flow

   https://doi.org/10.1111/mec.17509  

   Glover, Ashleigh_N; Sousa, Vitor_C; Ridenbaugh, Ryan_D; Sim, Sheina_B; Geib, Scott_M; Linnen, Catherine_R (August 2024, Molecular Ecology)

   Abstract Understanding the genetics of adaptation and speciation is critical for a complete picture of how biodiversity is generated and maintained. Heterogeneous genomic differentiation between diverging taxa is commonly documented, with genomic regions of high differentiation interpreted as resulting from differential gene flow, linked selection and reduced recombination rates. Disentangling the roles of each of these non‐exclusive processes in shaping genome‐wide patterns of divergence is challenging but will enhance our knowledge of the repeatability of genomic landscapes across taxa. Here, we combine whole‐genome resequencing and genome feature data to investigate the processes shaping the genomic landscape of differentiation for a sister‐species pair of haplodiploid pine sawflies,Neodiprion leconteiandNeodiprion pinetum. We find genome‐wide correlations between genome features and summary statistics are consistent with pervasive linked selection, with patterns of diversity and divergence more consistently predicted by exon density and recombination rate than the neutral mutation rate (approximated by dS). We also find that both global and local patterns ofF_ST,d_XYandπprovide strong support for recurrent selection as the primary selective process shaping variation across pine sawfly genomes, with some contribution from balancing selection and lineage‐specific linked selection. Because inheritance patterns for haplodiploid genomes are analogous to those of sex chromosomes, we hypothesize that haplodiploids may be especially prone to recurrent selection, even if gene flow occurred throughout divergence. Overall, our study helps fill an important taxonomic gap in the genomic landscape literature and contributes to our understanding of the processes that shape genome‐wide patterns of genetic variation. 

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2. Sensitivity of pair statistics on pair potentials in many-body systems

   https://doi.org/10.1063/5.0021475  

   Wang, Haina; Stillinger, Frank H.; Torquato, Salvatore (September 2020, The Journal of Chemical Physics)
3. Weighted matching with pair restrictions

   https://doi.org/10.1007/s11590-017-1217-7  

   Hochbaum, Dorit S.; Levin, Asaf (May 2018, Optimization Letters)
4. Turbulence in Magnetized Pair Plasmas

   https://doi.org/10.3847/2041-8213/aae483  

   Loureiro, Nuno F.; Boldyrev, Stanislav (October 2018, The Astrophysical Journal)
5. Linearized Pair-Density Functional Theory

   https://doi.org/10.1021/acs.jctc.3c00207  

   Hennefarth, Matthew R.; Hermes, Matthew R.; Truhlar, Donald G.; Gagliardi, Laura (June 2023, Journal of Chemical Theory and Computation)