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285 results for “Reproductive isolation”
Asynchronous life cycles contribute to reproductive isolation between two Alpine butterflies
<p>Data from: Asynchronous life cycles contribute to reproductive isolation between two Alpine butterflies</p> <p><strong>Abstract</strong></p> <p>Geographic isolation often leads to the emergence of distinct genetic lineages that are at least partially reproductively isolated. Zones of secondary contact between such lineages are natural experiments that allow investigating how reproductive isolation evolves and co-existence is maintained. While temporal isolation through allochrony has been suggested to promote reproductive isolation in sympatry, its potential for isolation upon secondary contact is far less understood. Sampling two contact zones of a pair of mainly allopatric Alpine butterflies over several years and taking advantage of museum samples, we show that the contact zones have remained geographically stable over several decades. Furthermore, they seem to be maintained by the asynchronous life cycles of the two butterflies, with one reaching adulthood primarily in even and the other primarily in odd years. Genomic inferences document that allochrony is leaky and that gene flow from allopatric sites scales with the degree of geographic isolation. Overall, we show that allochrony has the potential to contribute to the maintenance of secondary contact zones of lineages that diverged in allopatry.</p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p>Morphology contains the following files:</p> <p>wing_morpho.R<br> R scripts for data transformation of wing shape</p> <p>genital_morpho.R<br> R scripts for data transformation of genital morphology</p> <p><br> Models_used.R:<br> R scripts used to produce the statistical analyses.</p> <p>genital_morpho_master_with_pca.txt<br> Phenotypic data for genital morphology</p> <p>wing_contemporary_morpho_master_with_pca.txt<br> Phenotypic data for contemporary wing patterns</p> <p>wing_historic_morpho_master_with_pca.txt<br> Phenotypic data for wing patterns from museum samples</p> <p>The text files contains the following information:</p> <p>ID = Individual ID<br> genotyped_allopatric = was the individual genotyped<br> latitude<br> longitude<br> DATE = Date of collection<br> DAY = Day of collection<br> MONTH = Month of collection<br> YEAR = Year of collection<br> SPOT = Collection site<br> boxplotID = ID to reproduce boxplot order as used in the paper<br> colory = color code to plot<br> cycle = year cycle (2018/19 or 2020/21)<br> yeartype = even or odd year<br> genital_x_LM1 = linear measure of genital landmark 1 along the x axis<br> genital_y_LM1 = linear measure of genital landmark 1 along the y axis<br> genital_x_LM2 = linear measure of genital landmark 2 along the x axis <br> genital_y_LM2 = linear measure of genital landmark 2 along the y axis <br> genital_x_LM3 = linear measure of genital landmark 3 along the x axis <br> genital_y_LM3 = linear measure of genital landmark 3 along the y axis <br> genital_x_LM4 = linear measure of genital landmark 4 along the x axis <br> genital_y_LM4 = linear measure of genital landmark 4 along the y axis <br> genital_x_LM5 = linear measure of genital landmark 5 along the x axis <br> genital_y_LM5 = linear measure of genital landmark 5 along the y axis <br> v_t1 = length relationship between v and t1<br> v_t2 = length relationship between v and t2 <br> v_t3 = length relationship between v and t3 <br> t3_t1 = length relationship between t3_t1 <br> t3_t2 = length relationship between t3_t2 <br> t2_t1 = length relationship between t2_t1 <br> v_tg = length relationship between v and tg <br> PC1.x = PC1 axis for unprojected morphospace<br> PC2.x = PC2 axis for unprojected morphospace <br> PC3.x = PC3 axis for unprojected morphospace <br> PC4.x = PC4 axis for unprojected morphospace <br> PC5.x = PC5 axis for unprojected morphospace <br> PC6.x = PC6 axis for unprojected morphospace <br> PC7.x = PC7 axis for unprojected morphospace <br> PC1.y = PC1 axis for projected morphospace <br> PC2.y = PC2 axis for projected morphospace <br> PC3.y = PC3 axis for projected morphospace <br> PC4.y = PC4 axis for projected morphospace <br> PC5.y = PC5 axis for projected morphospace <br> PC6.y = PC6 axis for projected morphospace <br> PC7.y = PC7 axis for projected morphospace</p> <p> </p> <p><br> wing_ProcCoord1 = Procrustes coordinate 1<br> wing_ProcCoord2 = Procrustes coordinate 2<br> wing_ProcCoord3 = Procrustes coordinate 3<br> wing_ProcCoord4 = Procrustes coordinate 4<br> wing_ProcCoord5 = Procrustes coordinate 5<br> wing_ProcCoord6 = Procrustes coordinate 6<br> wing_ProcCoord7 = Procrustes coordinate 7<br> wing_ProcCoord8 = Procrustes coordinate 8<br> wing_ProcCoord9 = Procrustes coordinate 9<br> wing_ProcCoord10 = Procrustes coordinate 10<br> wing_ProcCoord11 = Procrustes coordinate 11<br> wing_ProcCoord12 = Procrustes coordinate 12<br> wing_ProcCoord13 = Procrustes coordinate 13<br> wing_ProcCoord14 = Procrustes coordinate 14<br> wing_ProcCoord15 = Procrustes coordinate 15<br> wing_ProcCoord16 = Procrustes coordinate 16<br> wing_ProcCoord17 = Procrustes coordinate 17<br> wing_ProcCoord18 = Procrustes coordinate 18<br> wing_ProcCoord19 = Procrustes coordinate 19<br> wing_ProcCoord20 = Procrustes coordinate 20<br> wing_ProcCoord21 = Procrustes coordinate 21<br> wing_ProcCoord22 = Procrustes coordinate 22<br> wing_ProcCoord23 = Procrustes coordinate 23<br> wing_ProcCoord24 = Procrustes coordinate 24<br> wing_ProcCoord25 = Procrustes coordinate 25<br> wing_ProcCoord26 = Procrustes coordinate 26<br> wing_ProcCoord27 = Procrustes coordinate 27<br> wing_ProcCoord28 = Procrustes coordinate 28<br> wing_ProcCoord29 = Procrustes coordinate 29<br> wing_ProcCoord30 = Procrustes coordinate 30<br> wing_ProcCoord31 = Procrustes coordinate 31<br> wing_ProcCoord32 = Procrustes coordinate 32<br> wing_ProcCoord33 = Procrustes coordinate 33<br> wing_ProcCoord34 = Procrustes coordinate 34<br> wing_ProcCoord35 = Procrustes coordinate 35<br> wing_ProcCoord36 = Procrustes coordinate 36<br> wing_ProcCoord37 = Procrustes coordinate 37<br> wing_ProcCoord38 = Procrustes coordinate 38<br> wing_ProcCoord39 = Procrustes coordinate 39<br> wing_ProcCoord40 = Procrustes coordinate 40<br> wing_ProcCoord41 = Procrustes coordinate 41<br> wing_ProcCoord42 = Procrustes coordinate 42<br> wing_ProcCoord43 = Procrustes coordinate 43<br> wing_ProcCoord44 = Procrustes coordinate 44<br> wing_ProcCoord45 = Procrustes coordinate 45<br> wing_ProcCoord46 = Procrustes coordinate 46<br> wing_ProcCoord47 = Procrustes coordinate 47<br> wing_ProcCoord48 = Procrustes coordinate 48<br> wing_ProcCoord49 = Procrustes coordinate 49<br> wing_ProcCoord50 = Procrustes coordinate 50<br> wing_ProcCoord51 = Procrustes coordinate 51<br> wing_ProcCoord52 = Procrustes coordinate 52<br> wing_ProcCoord53 = Procrustes coordinate 53<br> wing_ProcCoord54 = Procrustes coordinate 54<br> PC1.x = PC1 unprojected<br> PC2.x = PC2 unprojected<br> PC3.x = PC3 unprojected<br> PC4.x = PC4 unprojected<br> PC5.x = PC5 unprojected<br> PC6.x = PC6 unprojected<br> PC7.x = PC7 unprojected<br> PC8.x = PC8 unprojected<br> PC9.x = PC9 unprojected<br> PC10.x = PC10 unprojected<br> PC11.x = PC11 unprojected<br> PC12.x = PC12 unprojected<br> PC13.x = PC13 unprojected<br> PC14.x = PC14 unprojected<br> PC15.x = PC15 unprojected<br> PC16.x = PC16 unprojected<br> PC17.x = PC17 unprojected<br> PC18.x = PC18 unprojected<br> PC19.x = PC19 unprojected<br> PC20.x = PC20 unprojected<br> PC21.x = PC21 unprojected<br> PC22.x = PC22 unprojected<br> PC23.x = PC23 unprojected<br> PC24.x = PC24 unprojected<br> PC25.x = PC25 unprojected<br> PC26.x = PC26 unprojected<br> PC27.x = PC27 unprojected<br> PC28.x = PC28 unprojected<br> PC29.x = PC29 unprojected<br> PC30.x = PC30 unprojected<br> PC31.x = PC31 unprojected<br> PC32.x = PC32 unprojected<br> PC33.x = PC33 unprojected<br> PC34.x = PC34 unprojected<br> PC35.x = PC35 unprojected<br> PC36 = PC36 unprojected<br> PC37 = PC37 unprojected<br> PC38 = PC38 unprojected<br> PC39 = PC39 unprojected<br> PC40 = PC40 unprojected<br> PC41 = PC41 unprojected<br> PC42 = PC42 unprojected<br> PC43 = PC43 unprojected<br> PC44 = PC44 unprojected<br> PC45 = PC45 unprojected<br> PC46 = PC46 unprojected<br> PC47 = PC47 unprojected<br> PC48 = PC48 unprojected<br> PC49 = PC49 unprojected<br> PC50 = PC50 unprojected<br> PC51 = PC51 unprojected<br> PC52 = PC52 unprojected<br> PC53 = PC53 unprojected<br> PC54 = PC54 unprojected<br> PC1.y = PC1 projected<br> PC2.y = PC2 projected<br> PC3.y = PC3 projected<br> PC4.y = PC4 projected<br> PC5.y = PC5 projected<br> PC6.y = PC6 projected<br> PC7.y = PC7 projected<br> PC8.y = PC8 projected<br> PC9.y = PC9 projected<br> PC10.y = PC10 projected<br> PC11.y = PC11 projected<br> PC12.y = PC12 projected<br> PC13.y = PC13 projected<br> PC14.y = PC14 projected<br> PC15.y = PC15 projected<br> PC16.y = PC16 projected<br> PC17.y = PC17 projected<br> PC18.y = PC18 projected<br> PC19.y = PC19 projected<br> PC20.y = PC20 projected<br> PC21.y = PC21 projected<br> PC22.y = PC22 projected<br> PC23.y = PC23 projected<br> PC24.y = PC24 projected<br> PC25.y = PC25 projected<br> PC26.y = PC26 projected<br> PC27.y = PC27 projected<br> PC28.y = PC28 projected<br> PC29.y = PC29 projected<br> PC30.y = PC30 projected<br> PC31.y = PC31 projected<br> PC32.y = PC32 projected<br> PC33.y = PC33 projected<br> PC34.y = PC34 projected<br> PC35.y = PC35 projected</p> <p> </p> <p> </p> <p> </p> <p>Genomics contains the following files (Genomic data is available from NCBI BioProject: PRJNA1019795):</p> <p>all_euryale_calls.vcf.gz<br> The unfiltered VCF file</p> <p>euryale_V2.sh<br> Shell script for the genomic data analysis</p> <p>introgress.R<br> R script for running Introgress</p> <p>introgress_all_east2.txt<br> Output of Introgress for the Eastern contact zone</p> <p>introgress_all_west2.txt<br> Output of Introgress for the Western contact zone</p> <p>Admixture_output.txt<br> Output of Admixture assuming either 2 or 3 genomic clusters (K) with the respective population and ID</p> <p>Outliers2BombyxMori.txt<br> BLAST summary of outlier regions against Bombyx Mori</p> <p>Outliers2ManjolaJurtina.txt<br> BLAST summary of outlier regions against Manjola jurtina</p> <p>Outliers2ParargeAegeria.txt<br> BLAST summary of outlier regions against Pararge aegeria</p> <p> </p>
Data from: Do genetic loci that cause reproductive isolation in the lab inhibit gene flow in nature?
<p>The genetic dissection of reproductive barriers between diverging lineages provides enticing clues into the origin of species. One strategy uses linkage analysis in experimental crosses to identify genomic locations involved in phenotypes that mediate reproductive isolation. A second framework searches for genomic regions that show reduced rates of exchange across natural hybrid zones. It is often assumed that these approaches will point to the same loci, but this assumption is rarely tested. In this perspective, we discuss the factors that determine whether loci connected to postzygotic reproductive barriers in the laboratory are inferred to reduce gene flow in nature. We synthesize data on the genetics of postzygotic isolation in house mice, one of the most intensively studied systems in speciation genetics. In a rare empirical comparison, we measure the correspondence of loci tied to postzygotic barriers via genetic mapping in the laboratory and loci at which gene flow is inhibited across a natural hybrid zone. We find no evidence that the two sets of loci overlap beyond what is expected by chance. In light of these results, we recommend avenues for empirical and theoretical research to resolve the potential incongruence between the two predominant strategies for understanding the genetics of speciation.</p>
Data from: Inferring the evolution of reproductive isolation in a lineage of fossil threespine stickleback, Gasterosteus doryssus
<p>Darwin attributed the absence of species transitions in the fossil record to his hypothesis that speciation occurs within isolated habitat patches too geographically restricted to be captured by fossil sequences. Mayr's peripatric speciation model added that such speciation would be rapid, further explaining missing evidence of diversification. Indeed, Eldredge and Gould's original punctuated equilibrium model combined Darwin's conjecture, Mayr's model, and 124 years of unsuccessfully sampling the fossil record for transitions. Observing such divergence, however, could illustrate the tempo and mode of evolution during early speciation. Here, we investigate peripatric divergence in a Miocene stickleback fish, <em>Gasterosteus doryssus</em>. This lineage appeared and, over ~8,000 generations, evolved significant reduction of twelve of sixteen traits related to armor, swimming, and diet, relative to its ancestral population. This was greater morphological divergence than we observed between reproductively isolated, benthic-limnetic ecotypes of extant <em>Gasterosteus aculeatus</em>. Therefore, we infer that reproductive isolation was evolving. However, local extinction of low-armoured <em>G. doryssus</em> lineages shows how young isolate populations often disappear, supporting Darwin's explanation for missing evidence and revealing a mechanism behind morphological stasis. Exctinction may also account for limited sustained divergence within the stickleback species complex and help reconcile speciation rate variation observed across time scales.</p>
Can developmental plasticity shape sexual competition and promote reproductive isolation?
<p>Environmental factors such as dietary nutrients can shape the expression of developmentally plastic sexual traits in many species. However, while there has been extensive research into the developmental plasticity of sexual traits at the individual level, the broader consequences of this variation at the population scale remain poorly understood. Here, we asked whether plastic responses to the developmental environment can shape sexual competition and initiate reproductive isolation between populations. We reared neriid flies, <em>Telostylinus angusticollis</em>,<em> </em>on nutrient-rich and nutrient-poor larval diets, generating adult flies that differed in body size and secondary sexual trait expression. We then investigated sexual competition in experimental populations from each developmental environment, and tested for reproductive isolation between flies from mismatched environments. We found that, compared with poor-diet populations, rich-diet populations exhibited more frequent and escalated male-male combat and more frequent mating and mate-guarding. However, we found no evidence that sexual selection was affected by the developmental environment. Mismatched female-male pairs tended to take longer to mate and rich-diet females often rejected poor-diet males, but mismatched pairs were not less likely to mate within 1 hour or produce viable offspring. Our findings suggest that developmental plasticity could generate dramatic differences in sexual competition between populations, and could contribute to reproductive isolation.</p>
P-elements strengthen reproductive isolation within the Drosophila simulans species complex
Determining mechanisms that underlie reproductive isolation is key to understanding how species boundaries are maintained in nature. Transposable elements (TEs) are ubiquitous across eukaryotic genomes. However, the role of TEs in modulating the strength of reproductive isolation between species is poorly understood. Several species of Drosophila have been found to harbor P-elements (PEs), yet only D. simulans is known to be currently polymorphic for their presence in wild populations. PEs can cause reproductive isolation between PE-containing (P) and PE-lacking (M) lineages of the same species. Here, we use the simulans species complex to assess whether differences in PE status between D. simulans and its sister species, which do not harbor PEs, contribute to multiple barriers to gene flow between species. We show that crosses involving a P-D. simulans father and an M-mother from a sister species exhibit lower F1 female fecundity than crosses involving an M-D. simulans father and an M-sister-species mother. We also find that another TE, I-element, might play a minor role on determining the frequency of dysgenesis between species. Our results suggest that the presence of PEs in a species can strengthen isolation from its sister species, providing evidence that TEs can play a role in isolation. --
Differences in mating system and predicted parental conflict affect post-pollination reproductive isolation in a flowering plant
<p>Mating system shifts from outcrossing to selfing are frequent in plant evolution. Relative to outcrossing, selfing is associated with reduced parental conflict over seed provisioning, which may result in postzygotic, asymmetric, reproductive isolation in crosses between populations of different mating systems. To test the hypothesis that post-pollination reproductive isolation between populations increases with increasing differences in mating system and predicted parental conflict, we performed a crossing experiment involving all combinations of three self-compatible populations (with low outcrossing rates), and three self-incompatible populations (with high outcrossing rates) of the arctic-alpine herb Arabis alpina, assessing fitness-related seed and plant traits of the progeny. Predicted levels of parental conflict ("genome strength") were quantified based on strength of self-incompatibility and estimates of outcrossing rates. Crosses between self-compatible and self-incompatible populations yielded very small seeds of low viability, resulting in strong reproductive isolation. In 14 of 15 reciprocal between-population crosses, seeds were heavier when the paternal plant had the stronger genome, and seed mass differences between cross directions increased with an increased difference in parental conflict. Overall, our results suggest that, when sufficiently large, differences in mating system and hence in expected parental conflict may result in strong post-pollination reproductive barriers contributing to speciation.</p>
Evolution of reproductive isolation in a long-term evolution experiment with Drosophila melanogaster: 30 years of divergent life history selection
<p>We ask if three decades and over 1,500 generations of divergent life history selection on age at reproduction has resulted in the evolution of reproductive isolation (RI) between laboratory populations of <em>Drosophila</em> <em>melanogaster</em>. We tested for premating, postmating-prezygotic and postzygotic reproductive isolation between 3 replicate population pairs. Large evolved differences in body size between selection treatments suggested the potential for prezygotic barriers driven by sexual selection or physical incompatibilities between the sexes. Although a simple prediction would be preference for larger size, creating directional isolation, our results from individual mate choice trials indicate that populations from both selection treatments show a marked bias towards homotypic mate choice; indicative of prezygotic RI driven by sexual selection or sexual conflict. Hybridization between the focal populations resulted in the production of viable adult flies with intermediate size and developmental traits. We observed a suggestive but statistically non-significant trend of fitness decline in the F2 generation of hybrids, but no significant evidence suggesting the evolution of postmating-prezygotic or postzygotic RI. Our findings are in accord with extant literature that posits that premating RI evolves before postmating forms of RI.</p>
Evolution of reproductive isolation in a long-term evolution experiment with Drosophila melanogaster: 30 years of divergent life history selection
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Differences in mating system and predicted parental conflict affect post-pollination reproductive isolation in a flowering plant
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Data from: Rampant dispersal without gene-flow: Reproductively and geographically isolated lineages of the Supertramp lizard Lamprolepis smaragdina permeate the lesser Sunda Archipelago
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P-elements strengthen reproductive isolation within the Drosophila simulans species complex
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Data from: Mismatch between pollen and pistil size causes asymmetric mechanical reproductive isolation across Phlox species
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Data from: Cryptic female choice can maintain reproductive isolation
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Data from: Do genetic loci that cause reproductive isolation in the lab inhibit gene flow in nature?
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Data from: Inferring the evolution of reproductive isolation in a lineage of fossil threespine stickleback, Gasterosteus doryssus
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Data from: The evolution of a placenta accelerates the evolution of post-copulatory reproductive isolation
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Can developmental plasticity shape sexual competition and promote reproductive isolation?
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Adaptive zones shape the magnitude of premating reproductive isolation in Timema stick insects
<p>Simpson's fossil-record inspired model of 'adaptive zones' proposes that evolution is dominated by small fluctuations within adaptive zones, occasionally punctuated by larger shifts between zones. This model can help explain why the process of population divergence often results in weak or moderate reproductive isolation (RI), rather than strong RI and distinct species. Applied to the speciation process, the adaptive zones hypothesis makes two inter-related predictions: (i) large shifts between zones are relatively rare, (ii) when large shifts do occur they generate stronger RI than shifts within zones. Here we use ecological, phylogenetic, and behavioural data to test these predictions in <i>Timema </i>stick insects. We show that host use in <i>Timema</i> is dominated by moderate shifts within the systematic divisions of flowering plants and conifers, with only a few extreme shifts between these divisions. However, when extreme shifts occur they generate greater RI than do more moderate shifts. Our results support the adaptive zones model, and suggest that the net contribution of ecological shifts to diversification is dependent on both their magnitude and frequency. We discuss the generality of our findings in light of emerging evidence from diverse taxa that the evolution of RI is not always the only factor determining the origin of species diversity</p>
Data from: Vocal divergence is concordant with genomic evidence for strong reproductive isolation in grasshopper mice (Onychomys)
Behavioral barriers to gene flow often evolve faster than intrinsic incompatibilities, and can eliminate the opportunity for hybridization between interfertile species. While acoustic signal divergence is a common driver of premating isolation in birds and insects, its contribution to speciation in mammals is less studied. Here we characterize the incidence of, and potential barriers to, hybridization among three closely related species of grasshopper mice (genus Onychomys). All three species use long-distance acoustic signals to attract and localize mates; O. arenicola and O. torridus are acoustically similar and morphologically cryptic whereas O. leucogaster is larger and acoustically distinct. We used genotyping-by-sequencing (GBS) to test for evidence of introgression in 227 mice from allopatric and sympatric localities in the western United States and northern Mexico. We conducted laboratory mating trials for all species pairs to assess reproductive compatibility, and recorded vocalizations from O. arenicola and O. torridus in sympatry and allopatry to test for evidence of acoustic character displacement. Hybridization was rare in nature and, contrary to prior evidence for O. torridus/O. arenicola hybrids, only involved O. leucogaster and O. arenicola. In contrast, lab crosses between O. torridus
Genomic landscape of reproductive isolation in Lucania killifish: The role of sex loci and salinity
<p>Adaptation to different environments can directly and indirectly generate reproductive isolation between species. Bluefin killifish (<i>Lucania goodei</i>) and rainwater killifish (<i>L. parva</i>) are sister species that have diverged across a salinity gradient and are reproductively isolated by habitat, behavioral, extrinsic, and intrinsic postzygotic isolation. We asked if salinity adaptation contributes indirectly to other forms of reproductive isolation via linked selection and hypothesized that low recombination regions, such as sex chromosomes or chromosomal rearrangements, might facilitate this process. We conducted QTL mapping in backcrosses between <i>L. parva </i>and <i>L. goodei</i> to explore the genetic architecture of salinity tolerance, behavioral isolation, and intrinsic isolation. We mapped traits relative to a chromosome that has undergone a centric fusion in <i>L. parva</i> (relative to <i>L. goodei</i>). We found that the sex locus appears to be male determining (XX-XY), was located on the fused chromosome, and was implicated in intrinsic isolation. QTL associated with salinity tolerance were spread across the genome and did not overly co-localize with regions associated with behavioral or intrinsic isolation. This preliminary analysis of the genetic architecture of reproductive isolation between <i>Lucania</i> species does not support the hypothesis that divergent natural selection for salinity tolerance led to behavioral and intrinsic isolation as a byproduct. Combined with previous studies in this system, our work suggests that adaptation as a function of salinity contributes to habitat isolation and that reinforcement may have contributed to the evolution of behavioral isolation instead, possibly facilitated by linkage between behavioral isolation and intrinsic isolation loci on the fused chromosome.</p>
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