Transcriptome, Genetic Editing, and Microrna Divergence Substantiate Sympatric Speciation of Blind Mole Rat, Spalax

Transcriptome, genetic editing, and microRNA divergence substantiate sympatric speciation of blind mole rat, Spalax

Kexin Lia,b,1,2, Liuyang Wangc,1, Binyamin A. Knisbacher1, Qinqin Xue,1, Erez Y. Levanond, Huihua Wanga, Milana Frenkel-Morgensternf, Satabdi Tagoref, Xiaodong Fangg, Lily Bazakd, Ilana Buchumenskid, Yang Zhaob, Matej Lövyh, Xiangfeng Lii, Lijuan Hang, Zeev Frenkelb, Avigdor Beilesb, Yi Bin Caoj,2, Zhen Long Wangk,2, and Eviatar Nevob,2

aInstitute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing 100093, China; bInstitute of Evolution, University of Haifa, Haifa 3498838, Israel; cDepartment of Molecular Genetics and Microbiology, School of Medicine, Duke University, Durham, NC 27708; dThe Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan 52900, Israel; eThe People’s Hospital of Qinghai Province, Xining 810007, China; fFaculty of Medicine, Bar-Ilan University, Safed 13195, Israel; gBeijing Genomics Institute, BGI-Shenzhen, Shenzhen 518083, China; hDepartment of Zoology, Faculty of Science, University of South Bohemia, 37005 Ceske Budejovice, Czech Republic; iUniversity of Chinese Academy of Sciences, Beijing 100049, China; jCollege of Chemistry and Life Science, Zhejiang Normal University, Jinhua, Zhejiang 321004, China; and kSchool of Life Sciences, Zhengzhou University, Zhengzhou 450001, Henan, China

Contributed by Eviatar Nevo, May 18, 2016 (sent for review April 1, 2016; reviewed by Sergey Gavrilets and Morris Soller) Incipient sympatric speciation in blind mole rat, Spalax galili,in gene flow. The functions of selected genes adaptively met the di- Israel, caused by sharp ecological divergence of abutting chalk– vergent ecological stress very well, which suggests that natural se- basalt ecologies, has been proposed previously based on mito- lection overruled gene flow and drove ecological SS (5). Ecological chondrial and whole-genome nuclear DNA. Here, we present new speciation predicts that (i) population pairs from abutting divergent evidence, including transcriptome, DNA editing, microRNA, and ecologies have greater RI than those from similar but distant codon usage, substantiating earlier evidence for adaptive diver- ecologies (9, 10); (ii) adaptive divergence will limit genetic exchange gence in the abutting chalk and basalt populations. Genetic diver- between populations (11, 12), expediting RI evolution. Gene ex- gence, based on the previous and new evidence, is ongoing pression, both down- or up-regulation, and alternative splicing, play despite restricted gene flow between the two populations. The an important role in shaping the phenotype of organisms colonizing principal component analysis, neighbor-joining tree, and genetic a new environment (13). Consequently, it will enhance the adaptive structure analysis of the transcriptome clearly show the clustered spectrum, affecting genetic traits promoting RI. divergent two mole rat populations. Gene-expression level analy- DNA and RNA editing have the potential to accelerate sis indicates that the population transcriptome divergence is dis- genome evolution (14). DNA editing by apolipoprotein B mRNA- played not only by soil divergence but also by sex. Gene ontology editing enzymes, catalytic polypeptide-like (APOBECs), func- enrichment of the differentially expressed genes from the two abut- tions in various biological pathways in health and disease. In ting soil populations highlights reproductive isolation. Alternative genome defense, it restricts retroelements by introducing dele- splicing variation of the two abutting soil populations displays two terious hypermutation into the retroelement DNA synthesized distinct splicing patterns. L-shaped FST distribution indicates that the two populations have undergone divergence with gene flow. Tran- scriptome divergent genes highlight neurogenetics and nutrition Significance characterizing the chalk population, and energetics, metabolism, musculature, and sensory perception characterizing the abutting Speciation is the basis of the origin of biodiversity in nature. basalt population. Remarkably, microRNAs also display divergence Sympatric speciation (SS) is still a controversial model of the origin between the two populations. The GC content is significantly higher of new species, since first proposed by Darwin in 1859. Here, we in chalk than in basalt, and stress-response genes mostly prefer complement earlier genomic evidence with new analyses of tran- nonoptimal codons. The multiple lines of evidence of ecological– scriptome profiling, DNA editing, and microRNA, examined in the genomic and genetic divergence highlight that natural selection blind subterranean rodent, Spalax galili, in the Galilee Mountains, overrules the gene flow between the two abutting populations, Israel, all substantiating SS with gene flow. Gene ontology en- substantiating the sharp ecological chalk–basalt divergence driving richment of differentially expressed genes, in the abutting soil sympatric speciation. populations, highlights evolving reproductive isolation, despite a few interpopulation recombinants. Because sharply divergent natural selection | ecological adaptive speciation | DNA editing | geological, edaphic, climatic, and biotic interfaces abound in na- microRNA regulation | nonoptimal codon usage ture, we conclude that SS may be a common model of the origin of new species, as envisaged by Darwin. ympatric speciation (SS)—that is, speciation in a free breeding — Author contributions: E.N. designed research; K.L., E.Y.L., and E.N. performed research; Spopulation has been proposed by Darwin (1) but refuted by K.L., A.B., and Z.L.W. contributed new reagents/analytic tools; K.L., L.W., B.A.K., Q.X., Ernst Mayr, who accepted it later in life (2, 3). Four criteria are H.W., M.F.-M., S.T., X.F., L.B., I.B., Y.Z., M.L., X.L., L.H., Z.F., Y.B.C., and E.N. analyzed data; required for establishing SS: sympatry, reproductive isolation (RI), and K.L., L.W., B.A.K., M.F.-M., and E.N. wrote the paper. sister species, and no historical allopatry (4). However, whether all Reviewers: S.G., University of Tennessee; and M.S., Hebrew University of Jerusalem. these criteria could be detected in all of the emergent SS cases is The authors declare no conflict of interest. still unclear. Rising empirical (5) (SI Appendix, Suggested Reading) Data deposition: The sequences reported in this paper have been deposited in the Gen- Bank database (accession nos. SRP075890 and SRP075930). and theoretical studies (6, 7) demonstrated that SS may be common 1K.L., L.W., B.A.K., and Q.X. contributed equally to this work. in nature, although it is still being highly debated (4). Recently, we 2To whom correspondence may be addressed. Email: [email protected], demonstrated SS in the blind mole rat, Spalax galili,bybothmito- [email protected], [email protected], or [email protected]. chondrial genome (8) and by whole-genome resequencing (5), This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. demonstrating divergence across the whole genome with ongoing 1073/pnas.1607497113/-/DCSupplemental.

7584–7589 | PNAS | July 5, 2016 | vol. 113 | no. 27 www.pnas.org/cgi/doi/10.1073/pnas.1607497113 Downloaded by guest on September 30, 2021 during reverse transcription (among other mechanisms). In some transcriptome (Kolmogorow–Smirnov test, P = 0.002215), and cases, DNA-edited elements successfully enter the genome despite both of them appear as “L-shaped” (SI Appendix, Fig. S5). being hypermutated, containing a series of G-to-A mutations (15, The allele number of SNPs, which is defined as the total 16). These sequences enhance genomic diversity and, therefore, number of alleles in all individuals studied for that SNP at that increase the potential of developing new traits. A-to-I RNA site, was 1.60 and 1.58 in chalk and abutting basalt populations, editing by adenosine deaminases acting on RNAs (ADARs) respectively. It is significantly more in chalk than in basalt (P < enhances diversity through a different mechanism—it confers 0.00001). The heterozygosity of chalk and basalt populations are plasticity to the transcriptome by enabling a single mRNA iso- 0.1660 ± 0.2260 and 0.1454 ± 0.2220, respectively, and it is sig- form to give rise to a multitude of protein variants (17). nificantly more in the chalk population than in basalt (P < 2.2e-16, Here, we show SS in S. galili in upper Galilee, Israel, by tran- Wilcoxon test). scriptome divergence, DNA editing, microRNA regulation, and codon usage associated with the abutting but sharply divergent ecological Gene Expression Divergence Between the Two Mole Rat Soil Populations. environments, basalt and chalk, in the central eastern upper Galilee, A hierarchical cluster analysis was conducted based on the expres- Israel, complementing and reinforcing the genome divergence (5), sion level of 89,860 transcripts to estimate the contribution of sex thereby advancing our in-depth understanding of SS with gene flow. and environments to gene expression. Principal variance component analysis was also performed to estimate the expression divergence Results between the two soil populations (Fig. 1A). The first and second Transcriptome Sequencing and Population Divergence Analyses. The principal components (PCs) explain 55% and 17% expression var- subterranean blind mole rats, S. galili (SI Appendix, Table S1), iance, respectively. The largest PC1 separates the 10 animals by the were collected from the two abutting but sharply divergent rock, two sexes, and the second PC divided the animals (without the two soil, and vegetation types (SI Appendix, Fig. S1) for the present recombinants with larger basaltic genetic background) into two soil transcriptome study in 2014. Kinship of pairwise samples esti- chalk and basalt populations (Fig. 1A). The males, including SCN_7 mation show that the individuals used in the present study were (SCN, animals from chalk), SCN_9 from the chalk population, and not closely related (SI Appendix, Fig. S2). There are 30,928 SNPs SBN_9 (SBN, animals from basalt) from the basalt population (SI shared by both basalt and abutting chalk mole rat populations in Appendix,TableS1), were clustered into one group, whereas the seven females were clustered into another group (Fig. 1A). Another transcriptome, and 10,992 and 8,581 SNPs unique to basalt and + chalk populations, respectively (SI Appendix, Fig. S3A). Phylo- hierarchical cluster analysis of 1,600 transcripts from eight samples genetic tree analysis, principal component analysis (PCA), and a (without the two recombinants of SCN_1 and SCN_2) was con- maximum-likelihood analysis were performed using all of the ducted and shown in heatmap (Fig. 1B). There is no differentially SNPs called above, showing the genetic divergence in SS affect- expressed gene (DEG) between the chalk and basalt populations ing the entire transcriptome as it showed earlier in whole-genomic if the two recombinants were not removed. Individuals from the adaptive patterns between the soil divergent populations (5). In same soil could be clustered into their original soil clusters, although one individual from basalt (SBN_9) was not clear. phylogenetic analysis, animals from the same soil population were Pre-mRNA alternative splicing (AS) plays an important role in clustered together, and the two soil sister species, the chalk pro- enhancing genomic diversity in eukaryotes. In addition, the genetic genitor, and basalt derivative (5) were distinguished clearly by polymorphism will help to cope with environmental stresses (18). neighbor-joining (NJ) tree method (SI Appendix,Fig.S3B). In AS analysis demonstrates that all of the animals from the chalk PCA, all of the animals were clustered into two distinct groups (SI population, where they suffered the same environmental stresses, Appendix, Fig. S3C) corresponding to the two sibling species, and are grouped into one cluster (Fig. 1C); however, animals from the the first and second components explain 21.3% and 18.4% of the basalt population were divided to two subclusters (Fig. 1C). genetic variants, respectively. The variance is by far higher in the Genetic divergence in the face of gene flow was shown by the chalk population, possibly reflecting the much larger distance be- distribution of F . About 80% of the regions across the transcriptome tween territories and individuals, and the higher stress in the chalk ST display FST < 0.25.However,thereareafewregionsshowingbig EVOLUTION ecology (5, 8). In ancestral estimation analysis (SI Appendix,Fig. divergence with a value of F > 0.5 or even close to 1 (Fig. 1D). The S3D), population structure was estimated based on the maximum- ST = gene expression divergence and population differentiation measured likelihood model with varying K values. When assuming K 2, a by SNPs was weakly positively related (SI Appendix,Fig.S6). The clear division was observed between the 10 animals corresponding putatively selected genes were identified by using both F and to the two soil populations, which reflect the sharp ecological di- ST θπ (SI Appendix,Fig.S7). Interestingly, the gene OXNAD1 is re- vergence between chalk and basalt populations, as was also lated to oxidoreductase activity in the basalt population. obtained in the genome analysis (5) (see geological and vegetation divergence in SI Appendix, Fig. S1). When the K value was set to 3, Gene Ontology of the DEGs. Gene ontology (GO) enrichment was each of the chalk and basalt populations was separated into two performed using the gene ontology (GO) database (19) and the subpopulations but shared one subpopulation (in green in SI Ap- knockout mouse phenotypes ontology using Mouse Genome pendix,Fig.S3D), and one animal (SCN_2) was identified as a Informatics (MGI)–Mammalian Phenotype (MP) browser (20). recombinant, as was the case in the genome (5) and mitochondrial DEGs of the two abutting chalk and basalt populations were genome studies (6). When the K value was increased to 4, there characterized with knockout phenotypes affecting abnormal sex was also one recombinant (SCN_1) with genetic background from determination (MP0002210), of which the definition is an the two populations, and two shared subpopulations (SI Appendix, anomaly of primary or secondary sexual development or char- Fig. S3D). So, altogether, we identified two recombinants among the acteristics, abnormal male reproductive (MP0001145), which is 10 animals analyzed. In addition, both of them have a larger pro- defined as any structural anomaly of the organs associated with portion of basalt genetic background (SI Appendix, Fig. S3D). producing offspring in the gender that produces spermatozoa; Cross-validation (CV) error was calculated for each corres- abnormal sex gland (MP0000653), defined as any structural anomaly ponding K value. The number of groups, in other words, the proper of any of the organized aggregations of cells that function as secre- value of K, exhibits the lowest CV error compared with other K tory or excretory organs and are associated with reproduction; and values. In the present study, K = 2 shows the lowest cross-validation abnormal fertility/fecundity (MP0002161). Another two categories value, and we conclude that the animals could be clustered into two are related to morphology, including abnormal brain morphology distinct soil populations (SI Appendix,Fig.S4). The distributions (MP0002152) [defined as any structural anomaly of the brain, one of of FST values are highly congruent between the genome and the two components of the central nervous system and the center of

Li et al. PNAS | July 5, 2016 | vol. 113 | no. 27 | 7585 Downloaded by guest on September 30, 2021 AB

Fig. 1. Genetic and expression divergence in SS of S. galili.(A) PCA of gene-expression level of the 10 animals. Triangles denote males, and circles denote females. Animals from basalt were marked in red, and animals from chalk in blue. Animals marked by a white circle are the two recombinants. Note the separation of males and females; and the separation of chalk from basalt by a dashed line. (B) Hierarchical clustering analysis of differential expressed transcript (DET) between animals of the chalk and abutting basalt populations. (C) Hierarchical cluster analysis of alternative splicing variation of the 10 animals. All of the individuals from chalk were clustered into one group, and the animals from basalt were subdivided into two subclusters. Red bar denotes animals from basalt, and blue bar represent animals from chalk. (D)

The L-shaped FST distribution of the chalk and abutting basalt populations across the whole transcriptome. SBN, animals from basalt; SCN, animals from chalk.

thought and emotion; controls coordination, bodily activities, and the transcriptomes for DNA and RNA editing (SI Appendix, Meth- interpretation of information from the senses (sight, hearing, smell, ods) and identified both differential DNA and RNA editing. The etc.)] and mammalian phenotype (MP0000001). These gene screen for DNA editing revealed a total of 16,386 and 20,347 knockout mice exhibit abnormal reproduction. DNA-edited sites in basalt and chalk, respectively. Validity of The GO enrichment was performed on the 59 genes, which the DNA-editing sites was derived from the presence of the were identified from the FST outlier analysis, separating the expected rodent APOBEC3-editing preference (G-to-A muta- chalk and basalt abutting populations. We found similarity with tions in the GxA context) (16, 22) and by high ratios of G-to-A the genome results. These GO categories include energetics, over other mismatches (SI Appendix, Figs. S9 and S10). In- neurogenetics, nutrition, senses, metabolism, hypoxia, and mus- terestingly, most families (e.g., ERV1, ERVK) contained similar culature (SI Appendix,Fig.S8). rates of DNA editing in chalk and basalt populations; however, DNA- and RNA-Editing Comparison Between Spalax Chalk and Basalt ERVL had almost a fourfold increase in editing in the chalk Populations. Following the previous finding that DNA and RNA genome (4,140 edited sites; and only 1,168 in basalt; SI Appendix, editing are elevated in S. galili (21),wewereinterestedinexploring Fig. S11). This coincides with the previous observations of in- the possibility that they could have a role in SS. To do so, creased genetic diversity in molecular markers (AFLP), mtDNA, we comprehensively screened the basalt and chalk genomes and and whole genome in the ancestral chalk population (21).

7586 | www.pnas.org/cgi/doi/10.1073/pnas.1607497113 Li et al. Downloaded by guest on September 30, 2021 possible that yet-unidentified novel editing events in Spalax con- tribute to their speciation (Fig. 2).

MicroRNA Divergence in Regulation of the Chalk and Abutting Basalt Populations. MicroRNA plays main roles in responding to stresses through restoring or reprogramming gene expression patterns (24). MicroRNA was isolated from the same total RNA that were used for the transcriptome study above from mole rat populations of basalt and abutting chalk soils. Reads smaller than 18 bp or longer than 30 bp were removed from the downstream analysis. The generated data for each individual (BN6, BN9, CN1, and CN9) are 12.7M, 11.0M, 9.8M, and 12.5M (SI Appendix,TablesS3andS4), respectively. The length distribution of microRNA of each sample is shown in SI Appendix,Fig.S20. The first nucleotide bias and nucleotide bias at each site are shown in SI Appendix, Figs. S21 and S22. The number of matured, and pre-microRNA, as well as the number of kinds of noncoding RNA, and the number of noncoding microRNA are listed in SI Appendix,TablesS5andS6. MicroRNA expression level was estimated with 32 microRNA up- regulated, and 28 down-regulated in the basalt population (Fig. 3A and SI Appendix,Fig.S23). Target mRNA was predicted and GO Fig. 2. DNA-editing divergence of the chalk and basalt populations in SS. enrichment of differentially expressed target genes was performed. Interestingly, these GO categories include response to stimulus (GO:0050896), and cellular response to stimulus (GO:0051716), pro- To identify soil population-specific differences in RNA editing, tein dephosphorylation (GO:0006470), G-protein–coupled receptor two analyses were conducted—one of the major retroelement activity (GO:0004930), and signaling receptor activity. We found families (B1, B2, and B4) and the other of sites in mRNA known 614 microRNA shared by the two populations, and there are 30 and to be evolutionarily conserved RNA-editing targets in mammals 27 microRNA unique to basalt and chalk populations (Fig. 3B), (23) (SI Appendix). The former revealed that RNA editing is respectively. Three out of 27 from the chalk, and 5 of 30 micro- similarly prevalent in both soil types (SI Appendix, Figs. S12–S18). RNAs from the basalt are known, and the others are novel ones. However, the latter revealed two conserved sites with significantly Spalax altered editing levels between chalk and basalt populations Nonoptimal Codon Usage Preference in Stress-Response Genes. We have analyzed the codon preferences of the stress-response (χ2; false-discovery rate < 0.05). One resides in transmembrane genes in the two sibling species, i.e., in the chalk and abutting basalt protein 63B (TMEM63B) mRNA and was elevated in chalk soil populations. We found that stress response genes, identified in (68.6% vs. 60.6% in basalt), whereas the other is in insulin-like our previous paper (5), mostly prefer nonoptimal codons (SI Ap- growth factor binding protein 7 (IGFBP7) and was elevated in pendix,TableS7). We observed a consistent trend for the non- basalt (78.8% vs. 73.6% in chalk) (SI Appendix,Fig.S19andTable optimal codon usage preferences for both chalk and basalt soil S2). Although these changes are not severe, it cannot be ruled out populations. However, some preferences are significantly over- that such changes have functional impact. The current findings do represented for basalt populations. To verify the evolutionary not directly link DNA or RNA editing to speciation; however, the mechanism of the preferences observed, we submitted all of the editing sites identifiable with contemporary computational ap- stress-response genes for the GC content analysis. Interestingly, we

proaches are only a small fraction of all editing sites. Thus, it is found that chalk populations have significantly higher GC content EVOLUTION

Fig. 3. MicroRNA expression divergence of the chalk and abutting basalt populations. (A) Cluster analysis of differentially expressed microRNA in the chalk and basalt mole rat populations. (B) Venn diagram displaying the number of microRNA shared by the two mole rat populations, and unique to basalt and chalk populations, respectively.

Li et al. PNAS | July 5, 2016 | vol. 113 | no. 27 | 7587 Downloaded by guest on September 30, 2021 at the third position (SI Appendix,TableS8). We may speculate was explained by PC2 (17% variance). There are larger proportions that such GC content might be connected to the temperature of basaltic genetic background in the two recombinants of SCN_1 stress being higher in chalk than in basalt. and SCN_2 (SI Appendix,Fig.S3D), which may influence the gene expression level (25, 33) and the clustering of these two recombi- Discussion nant animals in the basalt group. This result suggests that envi- Population Genetic Divergence Analyses. The two mole rat soil ronmental stress affects the gene expression level, which facilitates populations that differentiated sympatrically and ecologically, SS with gene flow (13). There are no DEGs in the analysis with the are abutting, and the macroclimate there is completely the same. two recombinants, and differences are present only when the two As the animals are not from the same biological family, we can recombinants are removed (Fig. 1B). We could conclude that the assume that the divergence of the two abutting chalk and basalt DEGs are mainly caused by different genetic background rather populations derive from other reasons than family relationship. than due to transient plasticity. All of the genetic analyses, NJ tree (SI Appendix, Fig. S3B), PCA In the MGI database, the functions of all of the genes were (SI Appendix, Fig. S3C), and ancestry estimation (SI Appendix, verified by gene knockout experiments. The DEGs between the Fig. S3D) structure, showed clear divergence between the two abutting chalk and basalt populations were enriched to the on- soil mole rat populations. The chalk and abutting basalt populations tology categories from MGI database. Four of the ontology were clustered into their original soil types, respectively, which categories were related to RI, suggesting a possible ongoing RI precisely follows the sharp ecological divergence into basalt and reinforcement between the two populations. chalk ecologies (SI Appendix, Fig. S1) and the genetic divergence Two DEGs, ZGLP1 and APLP2, were found between the that was estimated in the previous studies of the whole genome chalk and abutting basalt populations. ZGLP1 is required for (5) and mitochondrial genome (8). In PCA (SI Appendix, Fig. ovary or granulosa cell development in various species (34, 35), S3C), the individuals from chalk were more scattered than that suggesting that this DEG possibly plays a role in RI, which will from basalt, probably because of stronger environmental stress expedite incipient SS; other DEGs are listed in Dataset S1. [less food resources and hotter temperature leading to fivefold sparser population density in chalk than basalt (8)]. These di- MicroRNA Divergence of the Chalk and Basalt Populations. Stresses vergent demographies (25) and ecologies, and higher environ- can harm the organisms by damaging the proteins, lipids, DNA, mental stresses in chalk than in basalt select for higher genetic and mRNA (24). Much genetic evidence indicates that microRNA diversity, leading to larger and more distinct territories as was plays important roles in adjusting stress responses (36). The GO shown by AFLP markers (26), mtDNA (8), and whole-genome enrichment of the target genes of the differentially expressed data (5). In ancestry estimation analysis (SI Appendix, Fig. S3D), microRNA between the chalk and abutting basalt shows the two there was a clear division between the two soil populations, as- populations are under different stresses. These responses may suming the K value of 2, demonstrating genetic divergence of the relate to regulation and adaptation of the mole rat populations. chalk and abutting basalt populations. One recombinant was miR-184 is one microRNA unique to chalk population, and this revealed by K = 3 (SCN_2) and a second recombinant by K = 4 microRNA plays an important role in neural stem cell prolifer- (SCN_1) (SI Appendix, Fig. S3D), respectively, suggesting on- ation and differentiation (37), which meet our previous results going gene flow and hybridization between the two soil pop- that chalk population is more developed in neurogenetics sys- ulations, conforming with the results of the mitochondrial tems (5). miR-615-5p is one of the microRNAs unique to basalt genome (8) and whole genome (5). Notably, natural hybrid zones population, and it plays an important role in suppressing cancer occur also between the four species of mole rats in Israel that (38), which is congruent with the more hypoxic environmental evolved peripatrically (27–29). basalt. Recombinants were found in chalk, which complements the genomic result suggesting that more animals migrate from basalt Conclusions and Prospects to chalk (5). The animals marked in blue (Fig. 1C) are mainly Is SS a rare or a common model of the origin of new species in from basalt. Even in the recombinant, there is a larger genetic nature? Our studies suggest that SS may be common in nature proportion from basalt, suggesting larger gene flow from basalt to wherever ecological contrasts abut. The current transcriptome, chalk. The cross-validation number was the smallest when K = 2 DNA editing, microRNA, and codon usage in the abutting eco- (SI Appendix,Fig.S4), suggesting that the chalk and abutting logically divergent chalk–basalt populations of S. galili highlight basalt mole rat populations diverged into two populations in the incipient SS. Natural selection in contrasting ecologies predomi- process of SS (5, 8). nates over homogenizing gene flow at a microsite. This previously Most of the genome regions display a relatively small di- unidentified multiple-line evidence complements and deepens vergence without substantial divergent selection between the earlier mtDNA and genomic evidence that SS is ongoing despite two abutting soil populations, which is in conformity with our restricted gene flow and hybridization between the abutting soil former genome discovery (5). The small part of genome regions populations. GO enrichment divergence of DEGs highlight re- with big divergence (large FST) is supposed to harbor genes productive isolation, and alternative splicing variations underline under divergent selection, and these genes may be related to contrasting populations’ adaptive evolution. Many biological reproductive isolation (30, 31). “L-shaped” FST distribution functions such as neurogenetics, nutrition, hypoxia, energetics, (Fig. 1D) was also predicted as a character of speciation with metabolism, musculature, and sensory perception are divergent gene flow (32). between the two soil populations. MicroRNA regulation and codon usage are also divergent between the evolving sibling Expression Level Comparison Between the Two Soil Populations. species. All of these predict that SS may be a common speciation SCN_1 and SCN_2 appear to be recombinants of the two sym- model because geological, edaphic, climatic, and biotic contrasts patrically originated mole rat populations (SI Appendix,Fig.S3D). abound in nature. This suggests the ongoing restricted gene flow between the two What next? A system approach to generating functional evo- populations, and the occurrence of SS with gene flow (5). The lutionary novelties seems highly recommended. The processes of basalt population is fivefold denser than the chalk population (8); nonrandom mutations, epigenetics, genome and transcriptome hence, the pressure of migration is from basalt to chalk, and as restructuring, and complex adaptive architecture, repetitive non- expected we found more recombinants in chalk (5, 8). The ex- coding DNA dynamics and regulation, and natural genetic engi- pression divergence of the two sexes was explained by PC1 (55% neering (39) could be profitably explored in SS. The environmental variance), and the expression divergence between the two soil types stresses and changes affecting the dynamic genome read–write

7588 | www.pnas.org/cgi/doi/10.1073/pnas.1607497113 Li et al. Downloaded by guest on September 30, 2021 involved in SS, under differential abutting stressful and contrasting alternative splicing were shown in the heatmap. DNA and RNA editing was ecologies, is a fertile ground for probing evolutionary dynamics of compared between the two populations. MicroRNA differences between the adaptation and speciation. two soil populations were displayed in both expression level and kinds of microRNA. Full details of the materials and methods are described in SI Materials and Methods Appendix, Methods. The experiments on animals in this study followed the rules and guidelines of the Ethics Committee of University of Haifa and Zhejiang Normal University. ACKNOWLEDGMENTS. We thank Huabin Zhao and Wei Hong for their Transcriptomes of animals from the two abutting soil S. galili populations contribution of genome sequence; and Shay Zur for his photo of the sampling site. The following foundations supported this work: the Agricul- were sequenced by Illumina HiSeq 2500. NJ tree, PCA, and maximum-likeli- tural Science and Technology Innovation Program (CAAS-ASTIP-2016-IAR), hood structure analyses were performed based on all of the SNPs. DEGs the Ancell–Teicher Research Foundation for Genetics and Molecular Evolu- between the chalk and abutting basalt soil populations were identified tion, the National Natural Science Foundation of China (Grants 31371209 and processed for GO enrichment. Heatmap and PCA were carried out and 31372193), the foundation of Henan Educational Committee (Grant on DEGs. The differences between the two abutting soil populations in 13A180717), and the Czech Science Foundation (Project 14-31670P).

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