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Experimental designConsortia of auxotrophic E. coli genotypes, which previously evolved an obligate mutualistic cooperation26, were used to determine how this type of interaction affects the ability of the participating individuals to respond to environmental selection pressures. To this end, two main experimental treatment groups were established. First, each of the two cooperative auxotrophs was grown as amino acid-supplemented monoculture (i.e. tyrosine and tryptophan, 100 µM each). Second, both genotypes were cocultivated in the absence of amino acid supplementation. A treatment, in which monocultures were cultivated in the absence of amino acid supplementation was not included, because auxotrophic genotypes would not grow under these conditions. Also, an amino acid-supplemented coculture was not implemented in the experimental design, because competition between both auxotrophs was likely to result in a loss of one of the two genotypes (Supplementary Fig. 1). Moreover, previous experiments showed that amino acid supplementation does not completely abolish the mutualistic interaction. Hence, the experiment compared monocultures with externally provided amino acids (i.e. no mutualism) to cocultures, which could only grow when strains reciprocally exchanged amino acids (i.e. mutualism). Replicate populations of both treatment groups were serially propagated while being subject to a stepwise increasing concentration of one of four different antibiotics (i.e. ampicillin, kanamycin, chloramphenicol, and tetracycline) (Fig. 1). These four antibiotics differed in their mode of action. In this way, not just the effect of a single stressor was probed, but rather the ability of mutualistic consortia to adapt to environmental stress in general.Ancestral consortia differ in their growth levels and susceptibility to environmental stressBefore the actual evolution experiment was performed, both growth levels and susceptibility to environmental stress was determined in the ancestral consortia. Comparing the maximum growth rate and densities populations achieved after 72 h revealed that unsupplemented cocultures grew significantly slower (Benjamini–Hochberg correction: P  More

Significance tests of straw return methods, potassium fertilization levels and their interactionsAnalysis of variance (ANOVA) results showed that straw return methods and potassium fertilization levels had significant effects on maize photosynthesis, dry matter and yield from 2018 to 2020 (Table 3). Significant interactions between straw return methods and potassium fertilization levels were only found on Pn of 2018 and 2020, and Tr of 2018–2020. Through the comparison of three-year F-values, it could be found that the effect of potassium fertilization levels on maize photosynthesis, dry matter and yield was greater than that of straw return methods.Table 3 Significance of the effects of straw return methods, potassium fertilization levels and their interactions on maize growth and yield using ANOVA.Full size tableEffects of straw return and potassium fertilizer on photosynthesis of maizeThe straw return methods and potassium fertilization levels significantly influenced (p ≤ 0.05) the maize photosynthesis compared to control (CK), resulting in Pn, Gs and Tr values that were higher than those of CK, and Ci value that was lower than that of CK.Straw return and potassium supply increased Pn, Gs and Tr. From 2018 to 2020, compared with CK, Pn increased by 1.70–4.09 under SFK0, 2.65–5.77 under SFK30, 5.21–8.48 under SFK45, 7.31–11.44 under SFK60, 0.63–3.20 under FGK0, 2.50–5.11 under FGK30, 3.60–5.79 under FGK45, and 3.97–7.47 μmol·m-2·s-1 under FGK60 (Fig. 1a). Gs increased by 0.60–0.90 under SFK0, 0.10–0.13 under SFK30, 0.18,-0.19 under SFK45, 0.20–0.22 under SFK60, 0.02–0.06 under FGK0, 0.08–0.09 under FGK30, 0.13–0.17 under FGK45, and 0.15–0.19 mmol·m-2·s-1 under FGK60 (Fig. 1b). Tr increased by 0.55–0.87 under SFK0, 1.02–1.30 under SFK30, 1.51–1.67 under SFK45, 1.74–1.99 under SFK60, 0.49–0.71 under FGK0, 0.86–1.13 under FGK30, 1.12–1.38 under FGK45, and 1.27–1.47 mmol·m−2·s−1 under FGK60 (Fig. 1c).Figure 1Effects of straw return methods and potassium fertilization levels on maize photosynthesis.Full size imageStraw return and potassium supply decreased Ci. From 2018 to 2020, compared with CK, Ci decreased by 5.43–8.92 under SFK0, 10.59–14.05 under SFK30, 19.04–21.21 under SFK45, 21.77–23.81 under SFK60, 2.26–6.52 under FGK0, 8.59–12.07 under FGK30, 12.93–16.15 under FGK45, and 17.81–19.46 μmol·mol-−1 under FGK60 (Fig. 1d).Comprehensive analysis showed that Pn, Gs, Tr increased and Ci decreased significantly after the treatment of SF under the same potassium supply. Under the same straw return method, Pn, Gs and Tr values increased significantly with the potassium fertilization levels, while Ci decreased. The effects of straw return and potassium fertilizer on maize photosynthesis increased gradually from year to year.Effects of straw return and potassium fertilizer on dry matter of maizeWe can see from Fig. 2, the straw return methods and potassium fertilization levels significantly increased (p ≤ 0.05) the maize dry matter accumulation. Compared with CK, under the treatments of SFK0, SFK30, SFK45, SFK60, FGK0, FGK30, FGK45 and FGK60, the dry matter of R1 and R6 stage increased by 1454.45, 2288.75, 3982.85, 4961.45, 1042.96, 1744.54, 2890.65, 3408.39 and 2152.43, 4433.55, 6726.72, 8051.51, 1195.76, 3337.79, 5121.77, 6247.56 kg/ha in 2018; the dry matter increased by 1812.69, 2959.44, 4370.19, 5615.94, 1545.06, 2238.06, 3421.11, 4028.64 and 2588.52, 5319.60, 7500.74, 8912.64, 1649.67, 3832.46, 6065.90, 6864.33 kg/ha in 2019; the dry matter increased by 2535.39, 3612.35, 5544.00, 6720.12, 2474.18,2827.94, 4749.86, 4769.66 and 3235.18, 5798.75, 8577.48, 10,071.83, 2515.75, 4386.39, 7256.61, 7536.91 kg/ha in 2020.Figure 2Effects of straw return methods and potassium fertilization levels on maize dry matter. Values followed by different letters in the same year indicated indicate statistical significance at α = 0.05 under different treatments. The same below.Full size imageIn short, under the same straw return method, the increase of maize dry matter from R1 to R6 improved significantly with the potassium level, potassium fertilizer could improve the maize dry matter accumulation ability. The maize dry matter of R1 to R6 increased significantly after the treatment of SF compared to FG under the same potassium supply. The promotion effect of straw return and potassium fertilizer on maize dry matter increased from year to year.Effects of straw return and potassium fertilizer on maize yieldThe straw return methods and potassium fertilization levels significantly influenced (p ≤ 0.05) the maize yield compared to CK, resulting in maize yield values that were higher than those of CK. Straw return and potassium supply increased maize yield. From 2018 to 2020, compared with CK, maize yield increased by 9.73–10.32% under SFK0, 15.68–17.47% under SFK30, 24.02–25.58% under SFK45, 24.46–25.76% under SFK60, 5.79–7.83% under FGK0, 13.51–13.72% under FGK30, 18.64–19.01% under FGK45, and 21.19–21.69% under FGK60 (Fig. 3).Figure 3Effects of straw return methods and potassium fertilization levels on maize yield.Full size imageThe maize yield among treatments was as follows: SFK60  > SFK45  > FGK60  > FGK45  > SFK30  > FGK30  > SFK0  > FGK0  > CK. Compared to FG, the effect of SF on maize yield was more obvious. The maize yield increased significantly with the potassium fertilization levels under the potassium fertilization levels of 0–60 kg/ha in this test. The treatment of SFK60 recorded the highest average yield in the three-year test, which was 14,744.39 kg/ha. The maize yield in different planting years showed as follows: 2020  > 2019  > 2018, which indicated that the promotion effect of straw return and potassium fertilizer on maize yield increased from year to year.Correlation analysis of photosynthesis, dry matter accumulation and yield of maizePn, Gs, Tr and Ci were significantly correlated with dry matter accumulation. Pn, Gs and Tr were positively correlated with dry matter, while Ci was negatively correlated with the dry matter (Table 4). The results showed that the increase of Pn, Gs, Tr and the decrease of Ci could significantly improve maize dry matter. Dry matter was positively correlated with maize yield, indicating that the increase of dry matter accumulation could significantly improve maize yield. The increase of Pn, Gs, Tr and dry matter accumulation, as well as the decrease of Ci, could significantly increase maize yield.Table 4 Correlation analysis of photosynthesis, dry matter accumulation and yield of maize under two straw return methods.Full size tableUnder the method of SF, the correlation coefficients of Pn, Gs, Tr, dry matter at R1 stage, dry matter at R6 stage and Ci with yield were 0.862, 0.988, 0.962, 0.948, 0.971 and −0.978; the correlation coefficients were 0.838,0.975,0.970,0.930,0.979 and −0.973 under the method of FG. The results showed that, under the method of SF, the correlation coefficients between dry matter of R1 stage, Pn, Gs, Ci with yield were higher than that under the method of FG, which indicated that SF could promote the correlation between the dry matter of R1 stage, Pn, Gs, Ci with yield. Under the method of FG, the correlation coefficients between the dry matters of R6 stage, Tr with yield were higher than that under the method of SF, which indicated that FG could promote the correlation between the dry matter of R6 stage, Tr with yield.Effects of straw return and potassium fertilizer on the profit of maize plantingGross income is an important economic index that determines the profit or benefit that a farmer can obtain. On the other hand, net return reflects the actual income of the farmer. According to the average selling price of maize (1 yuan/kg) from 2018 to 2020, the net income of maize planting of different treatments was as follows: SFK45  > SFK60  > FGK60  > FGK45  > SFK30  > FGK30  > SFK0  > FGK0  > CK (Table 5). Compared to CK. the average net profit of maize planting in the three-year test increased by 421.26, 1049.07, 2014.82, 1980.44, 313.58, 1035.34, 1587.44, 1828.69 yuan/ha between the treatments of SFK0, SFK30, SFK45, SFK60, FGK0, FGK30, FGK45 and FGK60. Straw return and potassium supply increased the net profit of maize planting. The net profit of maize planting increased significantly after SF compared to FG under the same potassium supply. The treatment of SFK45 reached the maximum profit of maize planting, which was 2014.82 yuan/ha.Table 5 Effects of straw return methods and potassium fertilization levels on the profit of maize planting.Full size table More

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Experimental animalsGymnocypris przewalskii used in this study were obtained from the Rescue Center for Naked Carp of Lake Qinghai in Xining. Only healthy fish without visible body damage were used. Wet mass and body length were recorded before the fish were sampled. All fish were collected under permits issued by local and national authorities, and experimental procedures were in accordance with national animal care regulations. Experimental waters were prepared daily, and water qualities were measured before each experiment. The water temperature and salinity were measured using an YSI6600 multiprobe sensor (YSI Incorporated, Ohio, USA), and the carbonate alkalinity was determined by titration39. All fish (average body weight: 33.21 ± 2.74 g; average body length:14.81 ± 0.35 cm) were held in an indoor RAS system at a density of approximately 6.5 kg m−3. The holding and experimental water were filtered tap water (Canature/AC/KDF150-1–300) (salinity 0.16, pH 7.56, carbonate alkalinity 2.7 mmol L−1, temperature 17.1 ± 0.61 °C). Fish were fed daily with commercial feed. Fish husbandry and experimental procedures were approved by the Second Scientific Research Ethics Committee of East China Sea Fisheries Research Institute.Experimental designFish were placed on a 14:10-h light:dark (5:00–19:00 with light intensity of 600–1000 lx; 19:00–5:00 with light intensity of 0 lx) photoperiod aquaculture system. To examine the effect of rhythm on osmoregulation and acid–base balance, this study measured four endpoints: drinking rate, self-feeding intake, mRNA expression and the single cell expression level of osmoregulation and acid–base regulation relevant proteins. Fish held in filtered tap water were transferred directly to saline-alkaline lake water with salinities of 15 (L15, salinity 14.83, pH 8.65, carbonate alkalinity 30.54 mmol L−1) and 17 (L17, salinity 16.80, pH 9.02, carbonate alkalinity 34.61 mmol L−1), which was prepared by adding the same ratio of NaCl, MgCl2.6H2O, Na2SO4, CaCl2, KCl, NaHCO3 and Na2CO3 as in Qinghai Lake. The experimental period was 4–5 days.Drinking rate during high saline-alkaline transferFish were placed on a 14:10-h light:dark (5:00–19:00 with light intensity of 600–1000 lx;19:00–5:00 with light intensity of 0 lx) photoperiod aquaculture system. In this experiment, feeding was stopped 48 h prior to the experiments. Fresh water fish were transferred directly to L15 and L17 PEG-4000 free water for up to 4 days. For drinking rate analysis, new tanks were prepared which contained 50L saline-alkaline lake water with salinity 15 or 17 and with PEG-4000 (final concentration was 1.00 g L−1) during the day (10:00–16:00) and night (4:00–22:00) on the fourth day respectively. Nine fish per treatment were individually transferred from PEG-4000 free water to each tank which contained 1.00 g L−1 PEG-4000 at 10:00 or 4:00. Water samples were collected at 15 min after the fish were transferred to each treatment group for the determination of PEG-4000 concentration. The fish were terminally anesthetized with MS-222 (0.40 g L−1) after 6 h. The intestines were then quickly dissected out from nine individual fish per treatment group and the intestinal fluid were collected and stored at 4 °C. All fish were weighed before sampling.Self-feeding intake during high saline-alkaline transferFish were placed on a 14:10-h light:dark (5:00–19:00 with light intensity of 600–1000 lx;19:00–5:00 with light intensity of 0 lx) photoperiod aquaculture system. In this experiment, fish were kept in freshwater (FW) or acclimated to L15 for more than 15 days before the experiment started. Six RAS glass tanks (95 cm × 60 cm × 60 cm), which belong to two circulatory systems (3 tanks for FW and 3 for L15), were used for self-feeding experiment. Each tank had 15 individuals.Before the experiment, fish were trained by a custom-made self-feeding system (Fig. S2). Trained fish triggered the self-feeder when they want to feed. In the self-feeding system, the photoelectric sensor converts the change of optical signal into the change of electrical signal, and the feeder release feed by recognizing level fluctuation.During the formal experiment, we collected feed data at 5:00 and 19:00, which were the time points of the light and dark transition. Feed intakes of naked carp were calculated by weighing the feed quantities at two time points. The experiment lasted 5 days.mRNA expression of osmoregulation and acid–base regulation relevant proteins during high saline-alkaline transferFish were placed on a 14:10-h light:dark (5:00–19:00 with light intensity of 600–1000 lx;19:00–5:00 with light intensity of 0 lx) photoperiod aquaculture system. In this experiment, feeding was stopped 48 h prior to the experiments. Fresh water fish were transferred directly to L17 for up to 4 days. There were 24 fish per tank in triplicate. At the fourth day, six fish per tank were individually removed and terminally anesthetized with MS-222 (0.40 g L−1) at 4:00, 10:00, 16:00 and 22:00, respectively. The mid-intestine was quickly dissected out from six individual fish at each time point. Mid-intestine tissues for mRNA expression analyses were immediately snap-frozen in liquid N2, and stored at − 80 °C until analysis.Single cell positive rate of osmoregulation and acid–base regulation relevant proteinsFish were placed on a 14:10-h light:dark (5:00–19:00 with light intensity of 600–1000 lx;19:00–5:00 with light intensity of 0 lx) photoperiod aquaculture system. In this experiment, feeding was stopped 48 h prior to the experiments. To analyze the single cell positive rate of acid–base relevant proteins, a separate experiment was conducted. Fresh water fish were transferred directly to L17 for up to 4 days. There were 3 tanks (6 fish per tank) in this experimental group. At the fourth day, three fish per tank were individually removed and terminally anesthetized with MS-222 (0.40 g L−1) at 16:00 and 22:00, respectively. The mid-intestine was quickly dissected out from nine individual fish and immediately prepared for single-cell suspensions.Analytical techniquesDrinking rate analysisThe measurement of drinking rate was performed according to the study of Buxton et al.40. After weighing the collected intestinal fluid, it was centrifuged at 13,000g for 1 min, and 50 μL of the supernatant was taken, added dropwise to 350 μL of 72% pre-cooled (4 °C) acetone, and vortexed to mix. Samples were then centrifuged at 2000g for 10 min at 4 °C, the supernatant filtered with 0.45 μm filter paper, followed by addition of 100 μL of filtrate to 175 μL 25 mg L−1 gum arabic and vortexed to mix. Finally, 200 μL of TCA-CaCl2 (trichloroacetic acid-calcium chloride, 30% and 5% by mass) was added to the mixture and the reaction allowed to proceed at room temperature for 20 min. An Epoch microplate (Bio Tek) spectrophotometry unit was used to measure the absorbance at 650 nm. The remaining solution was weighed again after drying at 60 °C for 48 h, and the volume of intestinal fluid was determined (quantity of collected intestinal fluid-mass after drying). The same method as above was used to process the standard solution. Solute concentrations for standard curve were prepared as 0.00 g L−1, 0.10 g L−1, 0.20 g L−1, 0.40 g L−1, 0.60 g/L−1, 0.80 g L–1, 1 g L−1, and 2 g L−1 PEG-4000. The PEG-4000 concentration of intestinal fluid was calculated based on the standard curve. Drinking rate (μLg-1h-1) = 1000 × (CI × VI)/(CW × W × t), where CI is the concentration of PEG-4000 in the intestinal fluid (gL-1), VI is the volume of intestinal fluid (mL), CW is the concentration of PEG-4000 in experimental water (gL-1),W is the body weight of the fish (g), t is the duration of the experiment (h).Molecular biologyThe known sequences of the NKA-α gene of naked carp were compared with the corresponding genes of other species in GenBank, and highly conserved regions were selected for primer design (Table 1). The reference gene EF1α was used according to Yao et al.3. Previously published primers were used for SLC26A6 and SLC4A4 genes6. After extracting total RNA with Trizol (Invitrogen), the integrity of RNA was detected by 1% agarose gel electrophoresis, and the concentration and purity of total RNA were determined by a Bio Tek Epoch microplate spectrophotometer. The Rever Tra Ace-α (TOYOBO) kit was used to reverse transcribe mRNA to cDNA. Fluorescence quantitative PCR analysis was performed using a QuantStudio™ Real-Time PCR (Thermo life) with the SYBR Premix Ex TaqIII (TaKaRa) kit: total reaction volume of 10 μL, including 5 μL SYBR Premix Ex Taq, 2 μL upstream primers, 2 μL downstream Primers, and 1 μL cDNA template. The amplification procedure was as follows: 95 °C 30 s, 1 cycle; 95 °C 5 s, 60 °C 20 s, 40 cycles. Three replicates were included for each sample, with EF1α as the internal reference gene. The relative expression of each gene was calculated using the 2−ΔΔCt method41. Melting curve analysis was performed following each reaction to confirm that there was only a single product and no primer-dimer artifacts. In addition, representative samples were electrophoresed to verify that only a single product was present. Negative control reactions were performed for representative samples using RNA that had not been reverse transcribed to control for the possible presence of genomic DNA contamination. No-template control reactions were also performed to verify the absence of contaminating DNA or primer-dimer amplification in the reactions.Table 1 Nucleotide sequences of the primers used for amplification.Full size tableSingle cell staining analysisThe naked carp mid-intestine was isolated and transferred to HBSS on ice. The mid-intestine was washed by HBSS (Corning, 21-022-CV) and transferred to pre-warmed digestion medium containing 0.2 mg·mL−1 Collagenase I (Gibco, 17100-017), 0.06 mg mL−1 Collagenase II (Gibco, 17101-015) and 0.2 mg mL−1 Collagenase IV (Gibco, 17104-019), which was shaken vigorously for 30 s and further incubated at 37 °C for about 30 min in incubator with gentle shaking every 5 min to release cells. Cells were then collected by centrifuging at 300 × g for 5 min, and resuspended in D-PBS (BBI, E607009-0500). Then taken an appropriate amount of single cell suspension and dropped it on poly-L-lysine-coated slides where the experimental area was drawn with a hydrophobic marker to allow the single cells to settle freely. When the cell sedimentation density was moderate, aspirated the excess cell suspension, slides were fixed with 4% paraformaldehyde fix solution (BBI, E672002-0500) for 10 min, and blocked with 3% BSA (Sigma, B2064) for 1 h, three washes in D-PBS. Subsequently, slides were incubated in NKA-α or SLC26A6 (antibody dilution ratio was 1:100) for overnight at 4 °C. The NKA-α antibody was a commercial polyclonal rabbit Na+/K+-ATPase α antibody (Santa Cruz Biotechnology, sc-28800). The SLC26A6 antibody was a commercial polyclonal rabbit SLC26A6 antibody (Abcam, ab-172684). After the incubation, three washes in D-PBS. The secondary antibodies consisted of Alexa flour 568 goat anti-rabbit IgG (Thermo Fisher Scientific, A11036) (antibody dilution ratio was 1:400). Slides were incubated in room temperature for 1 h, followed by three washes in D-PBS. Finally, incubate with Hochest for 30 min. Cells were then photographed with a fluorescence microscope. For every fish, positive protein expression was counted using at least three pictures. Image J was used to analyze the fluorescence intensity and record the positivity rate.Statistical analysisThe data was expressed as mean ± standard error (SE). Two-way ANOVA and One-way ANOVA with LSD multiple comparison were employed to compare drinking rate, food intake and relative gene expression among different treatments and time courses respectively. Differences in single cell positive rate between 16:00 and 22:00 in L17 were evaluated by chi-square test. Assumptions for all parametric models (normality and equal residuals) were assessed via diagnostic plots. Means were considered significantly different when P  More

Phylogenetic relations and systematics of AllactaginaeIntergeneric relationsOur data produced a robust phylogeny for Allactaginae above species level and thereby firmly proved that Allactaga s.l. (as recognised by Holden and Musser17) is paraphyletic to both Pygeretmus and Allactodipus. Both of the latter taxa are morphologically distinct from Allactaga by a number of unique apomorphies: a unique molar pattern and glans penis morphology in Allactodipus as well as high-crowned terraced molars, reduction of the premolar, and particular glans penis morphology in Pygeretmus. At the same time, the morphology of all other five-toed jerboas is relatively monotonous with variation only in terms of body size, relative molar crown height, size of auditory bullae, m1 morphotype frequency, and the rate of M3 reduction1,45. Such level of differences never allowed recognition of more than one genus.Thus, allactagines represent a case when descendant lineages with derived morphology are nested within a group with overall conserved morphology. This can be compared to paraphyly of white-toothed shrews Crocidura relative to Diplomesodon46, rorquals (Balaenoptera) relative to humpback whales (Megaptera)47, or tits (Parus s.l.) relative to morphologically aberrant ground tit (Pseudopodoces humilis)48. In such cases, the taxonomy should be changed in accordance with the monophyly principle, which is achieved by combining genera (as done in whales) or splitting the genus in question into new taxa (as done in tits). Unfortunately, any decision in this context is arbitrary as it is based on subjective weighting of morphological differences. For Allactaginae, the splitting approach was implemented18, which resulted in the elevation of Scarturus and Orientallactaga to the generic rank2, despite the fact that a synapomorphy-based morphological diagnosis of Scarturus can hardly be formulated.As an alternative to the morphology-based approach, temporal banding—a method which uses node age as a measure of rank49—was suggested as a standardised method for taxonomic ranking. In the present study, the age of divergence of major Allactaginae lineages was dated to the Pliocene. However, in other groups of Myodonta, Pliocene divergences were found both among genera (as in voles50 or hamsters51) and among congeneric species (as in Sicista52). Thus, the ambiguity remains unresolved; we see no better option than to retain the generic classification established by Michaux & Shenbrot2 (Table S10). However, it should be noted that the inferred age of divergence between S. tetradactylus + S. hotsoni and the VECE clades (3.9–4.1 Mya) is comparable or even larger than the divergence time of Allactodipus from Allactaga. If the temporal criterion (sensu Avise, Johns49) is accepted, one should consider elevating the VECE clade at least to subgeneric rank, with Scarturus proper including only two species. The diagnosis of the new taxon should be polythetic (medium to small jerboas with five-toes, bullae not enlarged, glans penis with longitudinal fold, molar low-to medium crowned, M3 not reduced). Although the name Paralactaga is traditionally used as a subgeneric for the S. euphraticus group and therefore may have been applied to the whole VECE clade, we believe that this is incorrect. The type species of Paralactaga—P. anderssoni Young, 1927—was described from the Late Miocene of China, which is inconsistent with the estimated time of origin of the VECE clade. Apparently all similarities between S. euphraticus group and Paralactaga proper are because of plesiomorphy. Therefore, we suggest that Paralactaga should be attributed to fossil taxa only.Species groups within ScarturusIn the present study, we analysed in detail the phylogenetic reconstructions and divergence times estimations for the species and species groups of the genus Scarturus. Our study is the first to examine the phylogenetic position of the enigmatic taxon described from Afghanistan and which is currently termed Scarturus williamsi caprimulga. The mitochondrial data provided clear evidence that this taxon is not closely related to any member of the S. euphraticus species group including S. williamsi. Instead, it belongs to a separate divergent lineage of Scarturus, which should be considered a separate species, Scarturus caprimulga. It also includes the jerboa from Kopet Dag provisionally classified by Hamidi et al25 as Paralactaga cf. williamsi. The mitochondrial difference between specimens from Afghanistan and those from Kopet Dag suggested a potential subspecies rank of the latter form, which is provisionally referred to as S. aff. caprimulga. More research on the distribution and genetic structure of this species is needed for further clarification. Our study has added more representative genetic data on the poorly known S. vinogradovi and confirmed it as a separate divergent branch within Scarturus s.l. and likely a distant sister group of S. caprimulga.Previous phylogenetic reconstructions of the S. euphraticus species group based on mtDNA data recovered a divergent branch within S. euphraticus53, which was subsequently classified as S. aulacotis2. With further addition of comprehensive nuclear data, the full species rank of this taxon is now completely supported. The relationships among the three species in the S. euphraticus group correspond to a hard trichotomy dated to the late Early Pleistocene.Nuclear data strongly support deep structuring within the S. elater species group, as previously demonstrated using mtDNA19,22,54, and confirmed the species status of S. indicus and S. heptneri. The divergence between S. elater and S. indicus estimated based on the nuclear loci was dated to approximately 1.5 Mya, which was slightly older than the 1.26 Mya inferred from mtDNA by Bannikova et al.22. Both S. indicus and S. elater included allopatric lineages that have separated 600–800 kya (i.e. dzungariae and strandi within elater, and aralychensis within indicus). Their formal taxonomic rank appears controversial: the level of divergence apparently conforms to species rank, whereas genetic data indicates potential gene flow between them. Thus, the mtDNA haplotypes of Scarturus specimens from the Zaisan depression (S. e. zaisanicus) form a subclade within S. elater s.str., whereas nuclear data suggest that S. e. zaisanicus is relatively close to S. e. dzungariae. This pattern suggests that the Zaisan population, while being a derivative of the Dzungar form, experienced mtDNA capture as a result of a past hybridisation event with S. elater. Gene flow between S. strandi and S. elater proper was indicated by the occurrence of elater mtDNA haplotypes in certain populations of strandi from north-western Kyzylkum22. All these taxa require additional research to produce a more accurate evaluation of gene flow intensity. Nevertheless, we suggest that dzungariae, strandi, and aralychensis should be considered semispecies or species in statu nascendi. Taxonomically, we regard them as parts of elater and indicus superspecies and refer to them as S. (elater) dzungariae, S. (elater) strandi, and S. (indicus) aralychensis, respectively.Phylogenetic relations within OrientallactagaWithin Orientallactaga, O. bullata and O. balikunica were supported as sister taxa based on nuclear data, which is consistent with their common morphology (enlarged bullae). However, mtDNA suggested that O. bullata is a sister taxon to O. sibirica, and the reason for this discrepancy is unclear, with ancient mtDNA introgression being the most obvious explanation. The crown age of Orientallactaga was dated to the early Early Pleistocene (Gelasian). Neither O. bullata nor O. balikunica show substantial intraspecific variation.In contrast, O. sibirica consists of several genetic lineages, which partly correspond to recognised subspecies. The mtDNA data tentatively supported subdivision of O. sibirica into western and eastern groups separated by the Tianshan–Altay zoogeographic boundary. The structure of variation in the eastern portion of the range (Mongolia, China) is well-studied23; however, the genetic data on the western portion are still fragmentary. Available mtDNA data provisionally support recognition of western subspecies such as O. s. ognevi (north-eastern to central Kazakhstan), O. s. dementjevi (Issyk-Kul region), and O. s. altorum (central Tianshan). The latter two forms are distributed in high-altitude areas of Tianshan, thus indicating that, in contrast to most other jerboa species, mountain areas might serve as foci of diversification in O. sibirica.The westernmost part of the range (western Kazakhstan, Qyzylkum) was assumed to be inhabited by a single O. s. suschkini subspecies after morphological revision1. However, three divergent mtDNA lineages were recovered based on the preliminary analysis of mtDNA data retrieved from museum specimens from the area, which suggests that the diversity of western populations is likely underestimated and in need of further examination.The crown age of O. sibirica was estimated at 500–600 kya, which was substantially younger than 2.2–3.2 Mya as inferred by Cheng et al.23; this discrepancy, however, can be explained by mtDNA saturation effects and usage of inaccurate secondary calibrations in their study.Variation within Allactaga and PygeretmusConsidering the phylogenetic position of Pygeretmus, our data firmly corroborated its separate phylogenetic position and rejected any affinity with Orientallactaga bullata as reconstructed by Wu et al.55. The latter result should be attributed to identification error. In our study, all three species of Pygeretmus were analysed to confirm phylogenetic proximity of P. shitkovi and P. platyurus relative to P. pumilio. Thus, the subgeneric status of Alactagulus containing the latter species was not contradicted; however, the split age between Pygeretmus s.str. and Alactagulus is relatively young, dated as Pliocene/Pleistocene boundary, indicating that morphological and life history traits of the former (e.g. slower locomotion) have evolved rather recently.A further taxon demonstrating a complex structure is Allactaga major. Our mtDNA data indicated that A. major consisted of several genetic lineages partly corresponding to morphological subspecies (A. m. spiculum, A. m. djetysuensis). A high level of divergence was observed between specimens from the northern Caucasus and Kazakhstan. A specimen of morphologically distinct A. m. spiculum (north-eastern Kazakhstan, western Siberia) was placed as a sister species to all other A. major with a divergence level compatible with species status.Several other species included unexpected genetic lineages that were apparently divergent at subspecies level (e.g. a southern Uzbekistan lineage of A. severtzovi and an Ili lineage of P. shitkovi). However, the resolving power of the employed set of 15 nuclear genes is insufficient for clarifying relationships within species. Therefore, these cases should be studied using larger samples and further nuclear loci.Divergence time estimates within AllactaginaeOur estimated divergence times were generally more recent than those produced by most previous studies. The root node of crown Allactaginae was dated to 7.7 (5.4–9.9) Mya by Wu et al.55, 8.1 (4.2–12.7) Mya by Zhang et al.56, or 8.87 (8.3–9.85) Mya by Pisano et al.4. The results by Wu et al.55 may be affected by a node density effect as their re-analysis with reduced taxon sampling of Allactaginae and Dipodinae produced younger dating at 5.8 (3.1–8.6) Mya. The latter two studies used only one to four nuclear loci and calibrated their analysis using non-Dipodidae calibration points. In both cases, the Early Miocene age of Sicista primus was used to calibrate crown Sicista, which lacks proper justification and may result in upward bias, as argued by Rusin et al.57.The earliest Allactaginae appeared in the Early Miocene and, in the Middle Miocene, the members of the primitive genus Protalactaga Young, 1927 became a common element of the Asian fauna3. During the Late Miocene, the diversity of allactagines persisted, and new genera emerged including Paralactaga Young, 1927 which is morphologically similar to Allactaga and is often considered its subgenus3,45. However, as can be derived from our results, all but one of the Middle and Late Miocene lineages went extinct without leaving any recent descendants, and all current diversity is a product of the Pliocene–Pleistocene evolution. This diversification pattern is unlike that observed in a different jerboa subfamily, Dipodinae, which includes lineages that had diverged in the Middle and early Late Miocene (Paradipus and Dipus, respectively)4,58.As estimated here, the onset of radiation among crown Allactaginae occurred in the latest Messinian and thus was nearly coincident with the Messinian crisis. However, it remains unclear how (or whether at all) climatic perturbations at the Miocene /Pliocene boundary affected the evolution of Allactaginae. The results of the diversification analysis suggested that, throughout the Pliocene and Pleistocene, the rate and mode of speciation in five-toed jerboas remained constant, indicating high tolerance of this group towards the climatic changes of this period.The minimum age of split observed between sympatric species was approximately 1 Mya as demonstrated by heptneri versus elater s.str. (and strandi). This was the estimate for the minimum time necessary for formation of effective reproductive barriers in allactagines (post- or pre-zygotic). Other phylogenetically close sympatric species pairs were S. elater/S. indicus (1.5 My), O. bullata/O. balikunica (1.5 My), and A. major/A. severtzovi (2.0 My).Geography of speciationOf 17 analysed episodes of speciation in Pliocene–Pleistocene, the patterns of range fragmentation in 10 episodes matched well to the classical vicariance scenario and those of six episodes matched to the founder-event speciation scenario; in one episode, both scenarios were equally probable. As the location of arising isolation barriers within the ancestor range seemed incidental, only in three cases the ancestors’ range was subdivided into two parts which were more or less equal in size: first, into East and West Central Asia; second, into Turan and Iran; third, into Anatolia with trans-Caucasus and northern Zagros and Levant with northern Mesopotamia and southern Zagros. In all other cases, the ancestors’ range was subdivided into the main part and relatively small peripheral isolates. As can be expected from the modern patterns of species diversity of Allactaginae, the discovered speciation events were unequally distributed: one episode in North Africa, one in the eastern part of Central Asia, three in the Middle East, four in the Iranian highland, four in Turan, and five in Kazakhstan. In most cases, range fragmentation coincided with extreme climate conditions within the analysed time periods: warmest and wettest (decrease of the area of arid lands: nodes 2–3, 5, 10, 12, and 14–15) or coldest and driest (closing narrow mountain passages due to mountain glaciation: nodes 4, 6–9, 13, and 16–18). In one case (node 11), fragmentation of the range coincided with moderate climate conditions.Successful modelling of fragmentation of geographic ranges as a base of speciation events seemed to agree with the hypothesis of Peterson et al.15, which states that ecological niches evolve little at or around the time of speciation events, whereas niche differences accumulate later. This hypothesis was supported by Peterson’s analysis59 of data published between 1999 and 2008 which demonstrated that niche conservatism was found in more than 70% of comparisons within species and between sister species, but in less than 50% of comparisons among closely-related (but not sister) species and across monophyletic lineages of species. Moreover, analysis of habitat niche evolution of arvicoline rodents16 demonstrated that closely related species with allopatric or parapatric distribution demonstrated small niche differences, whereas they were larger in species with sympatric distribution. This is a clear indication that interspecific competition forces natural selection to increase niche differences resulting in species co-occurrence. It was demonstrated that niche divergence/conservatism can be differently expressed between different niche/resource axes60. In voles, which have a highly specialised folivorous diet, habitat segregation seems to be the only type of niche differentiation. Closely related Allactaginae species are similar in diet and typically occur in allopatric or parapatric distribution patterns1, which may indicate their niche conservatism. The only exception to a pattern where species with similar diets show widely overlapping geographic distributions are Scatrurus elater and S. heptneri (these two species are similar in both, macro- and micro-habitat niches, and it is unclear which mechanisms allow them to co-occur22). Distantly related sympatric species typically show similarities regarding macro-habitat niches but marked differences in terms of micro-habitat niches (Allactaga major and Orientallactaga sibirica; O. sibirica and O. bullata; O. sibirica and O. balikunica; Pygerethmus pumilio and P. platyurus; P. pumilio and P. shitkovi; personal observations) and diet (Allactaga and Allactodipus; Allactaga and Scarturus; Allactaga and Pygeretmus; Orientallactaga and Pygeretmus; Scarturus and Pygeretmus1,61). Thus, macro-habitat niche conservatism may be expected even in sympatric species. More