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Figure 9. Dorsal habitus, females. A in Paraphyly and low levels of genetic divergence in morphologically distinct taxa: revision of the Pseudoanthidium scapulare complex of carder bees (Apoidea: Megachilidae: Anthidiini)

Figure 9. Dorsal habitus, females. A, vertex Pseudoanthidium nanum (Kalpetran, Switzerland); B, vertex P. scapulare (Rich, Morocco); C, mesonotum P. nanum (Kalpetran, Switzerland); D, mesonotum P. scapulare (Rich, Morocco); E, metasoma P. nanum (Kalpetran, Switzerland); F, metasoma P. scapulare (Rich, Morocco).

Figure 8. Lectotype Icteranthidium floripetum A in Paraphyly and low levels of genetic divergence in morphologically distinct taxa: revision of the Pseudoanthidium scapulare complex of carder bees (Apoidea: Megachilidae: Anthidiini)

Figure 8. Lectotype Icteranthidium floripetum A, face; B, dorsal view; C, labels; D, vertex; E, T1–T3.

Figure 7. Lectotype, Anthidium sinuatum. A in Paraphyly and low levels of genetic divergence in morphologically distinct taxa: revision of the Pseudoanthidium scapulare complex of carder bees (Apoidea: Megachilidae: Anthidiini)

Figure 7. Lectotype, Anthidium sinuatum. A, lateral view; B, labels; C, metasoma; D, T5–T6; E, mesonotum.

Figure 6 in Paraphyly and low levels of genetic divergence in morphologically distinct taxa: revision of the Pseudoanthidium scapulare complex of carder bees (Apoidea: Megachilidae: Anthidiini)

Figure 6. Palaearctic distribution of A, Pseudoanthidium nanum; B, P. scapulare; C, P. stigmaticorne; D, P. tenellum.

Figure 4. Lectotype, Pseudoanthidium reptans. A in Paraphyly and low levels of genetic divergence in morphologically distinct taxa: revision of the Pseudoanthidium scapulare complex of carder bees (Apoidea: Megachilidae: Anthidiini)

Figure 4. Lectotype, Pseudoanthidium reptans. A, face; B, dorsal view; C, labels; D, ventral view; E, apex of metasoma, showing tips of gonostyli.

Figure 2 in Paraphyly and low levels of genetic divergence in morphologically distinct taxa: revision of the Pseudoanthidium scapulare complex of carder bees (Apoidea: Megachilidae: Anthidiini)

Figure 2. Best-scoring maximum likelihood tree based on analysis of COI data. Numbers shown at nodes are maximum likelihood bootstrap values based on 1000 bootstrap replicates in RAxML. Only bootstrap values greater than 50% are shown. Terminals are labelled with a DNA extraction code, species name, collection locality and either as male (m) or female (f). Barcodes were obtained using Sanger sequencing technology, except for those corresponding to specimens 1802 and 1805, which were obtained from non-UCE assemblies generated during UCE sequencing. A, Pseudoanthidium tenellum, Burgenland, Austria (m), photo Bernhard Jacobi; B, P. cribratum, Bukhara, Uzbekistan (f), photo Jessica Litman; C, P. canariense, Santa Cruz de Tenerife, Canary Islands, Spain (m), photo Jessica Litman; D, P. stigmaticorne, Crimea, Russia, photo Alexander V. Fateryga; E, P. scapulare, Portugal, photo Ian Cross; F, P. nanum, photo Entomologie/Botanik, ETH Zürich / Albert Krebs; G, P. palestinicum, photo Jessica Litman.

opennotspecifiedJan 2015View details →

Figure 10 in Songs, genetics, and morphology: revealing the taxonomic units in the European Cicadetta cerdaniensis cicada group, with a description of new taxa (Hemiptera: Cicadidae)

Figure 10. Habitats of Cicadetta sibillae sp. nov. in Tiglieto (Liguria, A) and at the Monte San Giorgio (Ticino, B), and most important location of Cicadetta anapaistica lucana ssp. nov. in the mountainous Pollino National Park (C). Threatened core population habitat of Cicadetta anapaistica anapaistica in the Madonie Mountains as a result of overgrazing and soil erosion (D).

Figure 1. A in Paraphyly and low levels of genetic divergence in morphologically distinct taxa: revision of the Pseudoanthidium scapulare complex of carder bees (Apoidea: Megachilidae: Anthidiini)

Figure 1. A, nest of Pseudoanthidium stigmaticorne, in a capsule of Tulipa biflora Pall. (Lisya Bay, Crimea). Insert in lower right shows close-up of the same nest. Three males eventually emerged (photo Alexander V. Fateryga); B, Pseudoanthidium stigmaticorne nesting in a stem of Crambe maritima L. (Arabatskaya Strelka sand spit, Crimea). A pin is inserted to mark the nest (photo Sergey P. Ivanov).

Figure 3 in Paraphyly and low levels of genetic divergence in morphologically distinct taxa: revision of the Pseudoanthidium scapulare complex of carder bees (Apoidea: Megachilidae: Anthidiini)

Figure 3. Best-scoring maximum likelihood tree based on analyses of the (A) 75% UCE matrix and (B) 100% UCE matrix. Numbers shown at nodes are maximum likelihood bootstrap values based on 1000 bootstrap replicates in RAxML. Only bootstrap values greater than 50% are shown. Terminals are labelled with a DNA extraction code corresponding to the whole-body extraction performed for UCE sequencing, the DNA extraction code for the same specimen based on single leg extractions performed for barcode sequencing, the species name, collection locality and either as male (m) or female (f). Three specimens (1800, 1802 and 1805) were only sequenced following the UCE protocol and thus have only a UCE extraction code.

FIGURE 1 in Molecular genetics of Simulium (Wilhelmia) equinum (Linnaeus) (Diptera: Simuliidae) from West Siberia

FIGURE 1. The maximum likelihood phylogenetic tree (T92+G distances) for the COI DNA fragment for specimens sequenced in this study and for S. equinum and S. paraequinum from the DNA database. The branches, which do not include specimens from the Novosibirsk vicinity, were compressed. It was performed with 1000 iterations of bootstrap. The bootstrap values (percentages) are shown at the base of the branches (values less than 50% are not displayed).

FIGURE 2 in Molecular genetics of Simulium (Wilhelmia) equinum (Linnaeus) (Diptera: Simuliidae) from West Siberia

FIGURE 2. The typical electropherograms of the COI gene fragment restriction products of the black flies. A. BstF5 I enzyme, B. BspAC I enzyme (incomplete restriction). Lane 1: 100bp+1.5+3kb DNA marker; lane 6—the Finland-Turkish Branch; lanes 2–5, 7 and 8—the Novosibirsk Branch. Fragments less than 100 bp are not seen.

FIGURE 2 in Molecular investigation of the intra-specific genetic variation in Plantago ovata Forssk. (Plantaginaceae): An insight into potential ancestral area distribution and probable time of dispersal versus vicariance events

FIGURE 2 Combined RASP and chronological tree of BEAST for P. ovata accessions (The scale numbers are in MY).

FIGURE1 in Molecular investigation of the intra-specific genetic variation in Plantago ovata Forssk. (Plantaginaceae): An insight into potential ancestral area distribution and probable time of dispersal versus vicariance events

FIGURE1 TCS network of the studied P. ovata plants based on ITS sequences showing a higher level of nucleotide replacement within the Asiatic samples (Hatch marks indicate the number of mutations).

Panicum hallii RIL population (HAL2 X FIL2 ) genetic map

This project represents the method of constructing genetic map for the Panicum hallii Recombinant Inbreed Line (RIL) population. This population is a cross between one inland (HAL2) and one coastal (FIL2) natural accession of P. hallii. This map compromise of 441 RIL individuals genotyped for 901 markers. The raw sequences for RIL individuals are available in NCBI SRA archive Umbrella project PRJNA701489.

opencc-zeroSep 2022View details →

Phylogeography of a widely distributed plant species reveals cryptic genetic lineages with parallel phenotypic responses to warming and drought conditions

To predict how widely distributed species will perform under future climate change it is crucial to understand and reveal their underlying phylogenetics. However, detailed information about plant adaptation and its genetic basis and history remains scarce and especially widely distributed species receive little attention despite their putatively high adaptability. To examine the adaptation potential of a widely distributed species, we sampled the model plant Silene vulgaris across Europe. In a greenhouse experiment, we exposed the offspring of these populations to a climate-change scenario for central Europe and revealed the population structure through whole genome sequencing. Plants were grown under two temperature (18°C, 21°C) and three precipitation regimes (65 mm, 75 mm, 90 mm) to measure their response in biomass and fecundity related traits. To reveal the population genetic structure, ddRAD sequencing was employed for a whole genome approach. We found three major genetic clusters in S. vulgaris from Europe: one cluster comprising Southern European populations, one cluster of Western European populations and another cluster containing Central European populations. Population genetic diversity decreased with increasing latitude and a Mantel test revealed significant correlations between FST and geographic distances as well as between genetic and environmental distances. Our trait analysis showed that the genetic clusters significantly differed in biomass-related traits and in the days to flowering. However, half of the traits showed parallel response patterns to the experimental climate change scenario. Due to the differentiated but parallel response patterns, we assume that phenotypic plasticity plays an important role for the adaptation of the widely distributed species S. vulgaris and its intraspecific genetic lineages.

Plant growth over one growing season of Medicago truncatula in competition with conspecifics of different genetic relatedness

Kin recognition and kin selection have long been known to occur in animals where it shapes altruistic behavior towards relatives. More recently, studies have found that kin recognition and altered behavior towards kin can also occur in plants. However, inferring the underlying mechanism responsible for variation in plant performance in experimental studies is challenging as often, results can be explained by alternative and non-exclusive mechanisms such as niche differences, kin competition avoidance, and genetic variation in growth rate and competitive ability. Plant-plant interactions may change with the life stage of plants, and competition is often most intense towards the end of plants growing season. However, changes in plant-plant interaction intensity across plants life cycle are rarely considered in kin interaction studies. Here, we adapt a model of plant growth over time modified to specifically include effects of kin and non-kin competition. The model decompose competitive interactions at different stages during plant growth from initial growth to the end of the growing season. It estimates genotype specific variation in growth rate, and how sensitive individual genotypes are to competition neighbors. Furthermore, it estimates size asymmetry among plants accounting for both variation in growth rate, neighbor relatedness, and resource variation (here water availability). We use this model to analyze the results from a competition experiment where plants grew in mini-communities with neighbor plants that were either kin or non-kin. We find that when applied to our experiments, this approach can disentangle kin effects from other effects caused by genotypic variation in growth rate and competitive response to neighbors, and thus significantly help to detect whether plants exhibit kin-cooperative behavior

Interspecific hybridization and island colonization history, not rarity, most strongly affect the genetic diversity in a clade of Mascarene-endemic trees

Many factors shape the genetic diversity of island-endemic trees, with important implications for conservation. Oceanic island-endemic lineages undergo an initial founding bottleneck during the colonization process and subsequently accumulate diversity following colonization. Moreover, many island endemics occur in small populations and are further threatened by anthropogenic factors that cause population declines, making them susceptible to losses in genetic diversity through genetic drift, inbreeding, and bottlenecks. <a name="_Hlk80963234"></a>However, life-history traits commonly found in trees, such as outcrossing mechanisms, long lifespans, and a propensity for interspecific hybridization, may help buffer against losses of genetic variation. To assess the relative importance of colonization history, rarity, and distribution in shaping genetic diversity of island-endemic trees, we conducted a<a name="_Hlk80964566"></a> comparative population genomic analysis of 13 species of Diospyros (Ebenaceae) endemic to the Mascarene Islands that differ in island colonization history, distribution, population size, and IUCN threat status. We genotyped 328 individuals across the islands using 2b-RADseq, compared genetic diversity both among and within species, and assessed patterns of genetic structure. <a name="_Hlk80965008"></a>Genetic diversity did not vary significantly by IUCN status, but we found that species that co-occur with others on the same intermediate-aged island (Mauritius) had much greater genetic diversity than those that occur solitarily on an island (Réunion and Rodrigues), likely because of greater interspecific hybridization among species with overlapping distributions and processes related to time since island colonization. Results presented here were used to <a name="_Hlk80991503"></a>determine priority localities for in situ and ex situ conservation efforts to maximize the genetic diversity of each Mascarene Diospyros species.

Introgression, admixture and selection facilitate genetic adaptation to high-altitude environments in Chinese cattle

Domestication and subsequent selection of cattle to form breeds and biological types that can adapt to different environments partitioned ancestral genetic diversity into distinct modern lineages. Genome-wide selection particularly for adaptation to extreme environments left detectable signatures genome-wide. We used high-density genotype data for 42 cattle breeds and identified the influence of Bos grunniens and Bos javanicus on the formation of Chinese indicine breeds that led to their divergence from India-origin Zebu. We also found evidence for introgression, admixture, and migration in most of the Chinese breeds. Selection signature analyses between high-altitude (>1800m) and low-altitude adapted breeds (<1500m) revealed candidate genes (ACSS2, ALDOC, EPAS1, EGLN1, NUCB2) and pathways that are putatively involved in hypoxia adaptation. Immunohistochemical, real-time PCR and CRISPR/cas9 ACSS2-knockout analyses suggests that the up-regulation of ACSS2 expression in the liver promotes the metabolic adaptation of cells to hypoxia via the hypoxia-inducible factor pathway. High altitude adaptation involved the introgression of alleles from high-altitude adapted Yaks into Chinese B. t. taurus prior to their formation into recognized breeds and followed by selection. In addition to selection, adaptation to high altitude environments has been facilitated by admixture and introgression with locally adapted cattle populations.

opencc-zeroSep 2022View details →

Data from: Dietary stress unmasks cryptic genetic variation regulating lifespan in outbred Drosophila

Evolutionary theory suggests that lifespan-associated alleles should be purged from the gene pool, and yet decades of GWAS and model organism studies have shown they persist. Here, we address one potential explanation, the idea that the alleles that regulate lifespan do so only in certain contexts. We exposed thousands of outbred Drosophila to a standard and a high sugar diet. We then sequenced over 10,000 individuals and track genome-wide allele frequency changes over time, as these populations aged. We mapped thousands of lifespan-altering alleles, some associated with early- vs late-life tradeoffs, late-onset effects, and genotype-by-environment interactions. We find that lifespan-reducing alleles are most likely to be recently derived and have stronger effects on a high-sugar diet, consistent with the hypothesis that historically neutral or beneficial alleles can become detrimental in novel conditions. We also show that the gene midway, a regulator of lipid storage and ortholog of the lifespan-associated gene DGAT1 in mice, also regulates lifespan in Drosophila. Our results provide insight into the highly polygenic and context-dependent genetic architecture of lifespan, as well as the evolutionary processes that shape this key trait.