Aneuploidy in hexaploid wheat induces dysregulated gene expression due to the combined action of dosage effect, dosage compensation, and transcriptional response, which brings about diverse phenotypes.
Abstract
Aneuploidy, a condition of unbalanced chromosome content, represents a large-effect mutation that bears significant relevance to human health and microbe adaptation. As such, extensive studies of aneuploidy have been conducted in unicellular model organisms and cancer cells. Aneuploidy also frequently is associated with plant polyploidization, but its impact on gene expression and its relevance to polyploid genome evolution/functional innovation remain largely unknown. Here, we used a panel of diverse types of whole-chromosome aneuploidy of hexaploid wheat (Triticum aestivum), all under the common genetic background of cv Chinese Spring, to systemically investigate the impact of aneuploidy on genome-, subgenome-, and chromosome-wide gene expression. Compared with prior findings in haploid or diploid aneuploid systems, we unravel additional and novel features of alteration in global gene expression resulting from the two major impacts of aneuploidy, cis- and trans-regulation, as well as dosage compensation. We show that the expression-altered genes map evenly along each chromosome, with no evidence for coregulating aggregated expression domains. However, chromosomes and subgenomes in hexaploid wheat are unequal in their responses to aneuploidy with respect to the number of genes being dysregulated. Strikingly, homeologous chromosomes do not differ from nonhomologous chromosomes in terms of aneuploidy-induced trans-acting effects, suggesting that the three constituent subgenomes of hexaploid wheat are largely uncoupled at the transcriptional level of gene regulation. Together, our findings shed new insights into the functional interplay between homeologous chromosomes and interactions between subgenomes in hexaploid wheat, which bear implications to further our understanding of allopolyploid genome evolution and efforts in breeding new allopolyploid crops.
Aneuploidy in a broad sense includes the gain and/or loss of whole chromosomes, chromosome arms, or variable sizes of chromosomal segments (Tang and Amon, 2013). Nevertheless, the most frequent type of aneuploidy is whole-chromosome aneuploidy, which refers to conditions with excess and/or deficiency of some but not all the chromosomes and, hence, represents a severely imbalanced genome alteration. Consequently, the normal dosages of thousands of genes located on the aneuploid chromosome(s) are altered simultaneously, which produces profound effects on virtually all aspects of cellular physiology and often, but not always, impairs fitness (Torres et al., 2008; Williams and Amon, 2009; Rutledge and Cimini, 2016). Aneuploidy bears significant relevance to human health, as the condition is the leading cause of mental retardation and spontaneous abortion and a hallmark of cancer cells (Weaver and Cleveland, 2006). Aneuploidy also has been increasingly recognized as an important source of heritable variations and a driving force for rapid adaption by pathogenic microbial organisms under selective conditions (Pavelka et al., 2010), suggesting that an unbalanced karyotype, at least in some organisms under certain circumstances, can be adaptive.
Conceivably, an immediate impact of aneuploidy is on gene expression and, hence, altered abundance of gene products. Accumulated studies in model cellular systems and disparate organisms have established that aneuploidy can exert two broad types of impact on gene expression: (1) primary or cis-effects, that is, expression of the genes residing on the aneuploid chromosomes is altered due to dosage effects; and (2) secondary or trans-effects, that is, expression of a sizable portion of genes located on all the unvaried chromosomes is altered due to aneuploidy-induced activation and/or suppression of cellular pathways, a phenomenon dubbed the aneuploidy transcriptional response (Sheltzer et al., 2012; Birchler, 2014; Dürrbaum and Storchová, 2016). The molecular underpinnings of both the cis- and trans-effects on gene expression by aneuploidy remain to be fully understood (Birchler and Veitia, 2007; Dürrbaum and Storchová, 2016; Rutledge and Cimini, 2016). Meanwhile, dosage compensation also may occur, whereby the expression of certain genes located on some aneuploid chromosome(s) remains unchanged in spite of their copy number alterations (Guo and Birchler, 1994; Birchler et al., 2001; Hose et al., 2015; Gasch et al., 2016).
Model cellular aneuploid systems often concern only gain of chromosome(s), because the genetic background is either haploid or diploid, neither of which can usually sustain the loss of a whole chromosome (Rutledge and Cimini, 2016). For still mysterious reasons, plants in general are more tolerant to aneuploidy than animals. For example, in Arabidopsis (Arabidopsis thaliana), selfed progeny of a triploid mother plant generates a swarm of diverse types of aneuploid plants that are viable and fertile (Henry et al., 2007; Huettel et al., 2008; Henry et al., 2010; Matsushita et al., 2012). Moreover, many plant species are polyploids, which in theory have a much greater capacity to buffer the dosage imbalance of individual chromosome gain or loss and, therefore, are more permissive to the occurrence of whole-chromosome aneuploidy than diploids, especially for chromosome loss.
Notably, aneuploidy is frequently associated with nascent polyploidization in plants (Xiong et al., 2011; Chester et al., 2012; Zhang et al., 2013b); however, whether these are ephemeral by-products of whole-genome duplication or represent an important contributing factor to polyploid genome evolution, especially at the onset stage of polyploid formation, remains uninvestigated. However, the latter possibility is likely, given that, in contrast to nucleotide mutation, many types of aneuploidy can be readily reverted back to euploidy following subsequent meiotic segregation yet might as well impart their impacts (heritable variation in gene expression) to the euploid progeny (Henry et al., 2010; Gao et al., 2016). Therefore, studying aneuploidy in plants under a polyploid genomic environment not only allows assessing the effects of both chromosome gain and loss to a greater dosage amplitude but also may provide insights into the relevance of aneuploidy to polyploid genome evolution. There is an added significance to this line of study, because whole-genome duplication is a pervasive driving force in the evolution of all higher plants (Doyle et al., 2008; Van de Peer et al., 2009; Jiao et al., 2011; Estep et al., 2014).
Common wheat (Triticum aestivum; 2n = 6x = 42, genome BBAADD) is a young allohexaploid species (approximately 8,500 years old) harboring three closely related but distinct subgenomes with limited intersubgenomic exchanges (Sears, 1944; Feldman et al., 1995). Wheat stands as a textbook example of speciation via allopolyploidization as well as one of the most successful staple food crops humans have ever domesticated (Feldman et al., 1995; Dubcovsky and Dvorak, 2007). Probably due to its hexaploid nature and high level of functional redundancy (due to homeology) among the three subgenomes, common wheat can host a repertoire of diverse whole-chromosome aneuploidy. In fact, various types and often a complete set (i.e. concerning all 21 chromosomes) of aneuploid strains were developed successfully in wheat decades ago (Sears, 1944). Being an established species and a remarkably productive crop, the three subgenomes (A, B, and D) of wheat are apparently coexisting and functioning in harmony, which has been suggested to be due, at least in part, to the extensive genomic changes that occurred immediately after the allopolyploidization events (Feldman et al., 2012; Pont et al., 2013; El Baidouri et al., 2017), which include the nearly ubiquitous occurrence of whole-chromosome aneuploidy (Zhang et al., 2013b). Transcriptome analysis indicated that the three subgenomes of wheat show a high degree of cell type- and stage-dependent subgenome expression dominance, suggesting specification, asymmetry, as well as interplay among the three subgenomes at the transcriptional gene regulation level (Pfeifer et al., 2014). In contrast, the fact that the BBAA component of wheat can be extracted out to form viable and fertile plants suggests the still genetic integrity and functional independence of the subgenomes (Kerber, 1964; Zhang et al., 2014). However, the extent to which the three subgenomes of wheat are concordantly or independently regulated at the gene expression level within the common nucleus of hexaploid wheat remains an unresolved issue.
In this study, a panel of diverse types of whole-chromosome aneuploidy, including variable doses of whole-chromosome gain, loss, or concomitant gain and loss of homeologous chromosomes, primarily of the homeologous group 1 (i.e. chromosomes 1A, 1B, and 1D) as representatives, was chosen to systemically investigate the dosage sensitivity, transcriptional responses, and possible dosage compensation of whole-chromosome aneuploidy in hexaploid wheat. The choice of the homeologous group 1 whole-chromosome aneuploidies as representative is primarily because they do not possess known special properties with respect to the impact of aneuploidization on genome-wide gene expression in hexaploid wheat. All studied aneuploid strains were in the common genetic background of the laboratory standard genotype, cv Chinese Spring (CS), of wheat, originally developed by Sears (1944); hence, all are isogenic. In comparison with prior findings in haploid or diploid aneuploid systems, we unravel novel features of gene expression associated with the two major impacts of aneuploidy (i.e. cis- and trans-effects) as well as dosage compensation. Especially, we document the striking observation that homeologous chromosomes did not show differences from nonhomologous chromosomes with respect to transcriptional responses to whole-chromosome aneuploidy, irrespective of the aneuploid chromosome(s) being loss, gain, or simultaneous loss/gain, or at different dosage gradients. This finding strongly suggests regulatory autonomy at the transcriptional level of the three subgenomes in hexaploid wheat, which may shed new light on our understanding of the gene regulatory orchestration of the three constituent subgenomes of hexaploid wheat and which also may bear implications in allopolyploid crop amelioration via genetic editing or targeted (sub)genomic selection.
RESULTS
Karyotype Verification for All Aneuploid Strains and Their Common Isogenic Euploid Wild Type of Hexaploid Common Wheat
Aneuploid chromosomes, being numerically unbalanced, are intrinsically unstable during meiotic transmission. Moreover, the aneuploid condition per se may promote chromosome missegregation of the normal chromosomes in meiosis and/or mitosis, producing lagging chromosomes, and, hence, induce additional and ongoing numerical and structural chromosome changes, a process collectively termed chromosome instability (Sheltzer and Amon, 2011). Thus, to ensure the accuracy of the analyzed plants, we first set out to verify the karyotypes of all the used aneuploid strains of hexaploid common wheat CS and their isogenic wild-type euploid by a sequential genomic in situ hybridization (GISH)/fluorescence in situ hybridization (FISH) karyotyping method (Zhang et al., 2013b). This method enables reliable identification of all 21 homologous chromosome pairs in hexaploid wheat (Zhang et al., 2013b; Fig. 1; Supplemental Fig. S1). Therefore, this analysis not only ensures correct karyotypes of the aneuploid strains to be analyzed but also safeguards the exclusion of any additional karyotypic variations due to chromosome instability, which would confound the results. Karyotypes of all individual plants constituting each of the 10 distinct whole-chromosome aneuploid strains in the common genetic background of CS are validated (Fig. 1; Supplemental Fig. S1; Supplemental Table S1), which were found to contain no additional numerical and structural chromosome aberrations either at the whole-plant or cell level (somatic mosaic aneuploidy). The bona fide euploid karyotype for each used individual of the euploid wild type (CS) also was verified (Fig. 1).
Figure 1.
Diagrammatic illustration of all 10 karyotypes of whole-chromosome aneuploid strains in hexaploid wheat used in this study. Based on sequential GISH and FISH, all 21 homologous chromosome pairs in hexaploid wheat can be reliably discriminated (Zhang et al., 2013b). The center image depicts the FISH and GISH profiles of the euploid wild-type hexaploid wheat (CS), illustrating the karyotyping method (bar = 10 μm). A to J are diagrams for the 10 aneuploid strains, which include monosomic 1A (A), monosomic 1B (B), monosomic 1D (C), trisomic 1A (D), tetrasomic 1A (E), monosomic 2A (F), trisomic 2A (G), nullisomic 1A (H), nullisomic 1A/trisomic 1B (I), and nullisomic 1A/tetrasomic 1B (J). The aneuploid chromosome(s) in each aneuploid strain is underlined. In GISH, genomic DNAs of Triticum uratu (AA) and Aegilops tauschii (DD) were used as probes, while genomic DNA of Aegilops speltoides (SS) was used as a blocker. In FISH, two repetitive DNA sequences, pSc119.2 (green) and pAS1 (red), were used as probes. Original images of all 10 aneuploid karyotypes are shown in Supplemental Figure S1.
All the Studied Diverse Types of Whole-Chromosome Aneuploidy in Hexaploid Wheat Induce Dysregulated Gene Expression via cis- and trans-Effects
We assessed the impact of the diverse types of whole-chromosome aneuploidy, all under the same hexaploid common wheat (CS) genomic environment, on genome-wide gene expression with respect to both genes residing on the numerically altered chromosomes (i.e. cis-effect) and those on the unvaried chromosomes (i.e. trans-effect) in a given aneuploid strain. We conducted deep mRNA sequencing (RNA-seq)-based transcriptome profiling for the second fully expanded leaf tissue of third-leaf-stage seedlings (Simmons et al., 1985) of each of the 10 aneuploid strains (Fig. 1; Supplemental Table S1) along with their common isogenic euploid strain (CS), with biological replicates (see “Materials and Methods”). We first conducted an assessment for possible differences in transcriptome size between an aneuploid strain and CS or among the aneuploid strains by the method reported (Coate and Doyle, 2010; Matos et al., 2015). We found that there are no statistically significant differences in transcriptome sizes in all pairwise comparisons involving seven analyzed aneuploid strains and CS (data not shown but available upon request). We calculated the FPKM (fragments per kilobase of gene per million mapped reads) values to quantify normalized chromosome- and genome-scale gene expression changes (i.e. dysregulated expression) due to the various types of whole-chromosome aneuploidy. Through pairwise comparisons of each aneuploid strain versus the common isogenic euploid CS, we obtained the following major observations.
First, the four types of aneuploidy involving the same chromosome 1A (i.e. nullisomic 1A [designated N1A, referring to missing a pair of chromosomes 1A], monosomic 1A [designated M1A, referring to loss of one chromosome 1A], trisomic 1A [designated Tri1A, referring to gaining one extra chromosome 1A], and tetrasomic 1A [designated T1A, referring to gaining a pair of chromosomes 1A]) all caused dysregulated expression via both cis- and trans-effects relative to their isogenic euploid (CS), but to substantially variable magnitudes (Fig. 2A). Specifically, compared with CS, N1A exhibited the largest trans-effect (cis-effect is not applicable for this strain due to the complete absence of chromosome 1A), with the expression of 4,603 genes (9.42% of all expressed genes) being altered significantly (χ2 test, all q < 8.41E-177; Fig. 2A; Supplemental Table S2). M1A showed the second largest effect, with the expression of 2,262 genes (4.5%) being affected, of which 730 and 1,532 were due to cis- and trans-effects, respectively (Fig. 2A; Supplemental Table S2). T1A showed a similar effect to M1A, with the expression of 2,221 genes (4.4%) being affected, of which 666 and 1,555 were due to cis- and trans-effects, respectively (χ2 test, q = 0.525; Fig. 2A; Supplemental Table S2). Tri1A showed the smallest effect, with the expression of only 726 genes (1.47%) being affected, of which 225 and 501 were due to cis- and trans-effects, respectively (χ2 test, all q < 1.08E-161; Fig. 2A; Supplemental Table S2). Together, the most dramatic or unanticipated results from the above comparisons are as follows: (1) missing the whole pair of chromosomes 1A (N1A) has the largest effect, which makes all other studied aneuploidies pale in this respect; (2) gain of one extra chromosome 1A (Tri1A) has a much smaller effect (actually the smallest effect; detailed in later sections) than gain of a pair of extra chromosomes 1A (T1A); and (3) loss exerts a much greater trans-effect than gain of the same dose for the same chromosome (1A). We should caution, however, that these characteristics might bear chromosome specificity and, therefore, may not completely hold true for all the wheat chromosomes.
Figure 2.
Impact of whole-chromosome aneuploidy on global gene expression in hexaploid wheat. A, Numbers of dysregulated genes in each of the aneuploid strains relative to their common euploid wild type (CS). Based on chromosomal location, the dysregulated genes in each aneuploid strain can be classified into a cis-effect group (mapped to the aneuploid chromosomes) and a trans-effect group (mapped to the unvaried chromosomes), and these are represented by black and gray bars, respectively. B, Hierarchical analysis of dysregulated genes from the aneuploid strains and their common euploid CS, based on the expression pattern of genes (12,565 in total) that showed dysregulated expression in at least one of the aneuploid strains. The height shows the correlation distance among the strains. Green and red numbers are significances determined via normal bootstrapping (bootstrap probability [bp]) and multiscale bootstrapping resampling (approximated unbiased P value [au]), respectively. C, Heat map visualizing the hierarchical clustering of gene expression levels in each strain. The color key is indicated at the bottom.
Second, the same type of aneuploidy (i.e. monosomic) of the three chromosomes belonging to a given homeologous group (group 1) exhibited similar but also dramatically different cis- and/or trans-effects on transcript abundance (Fig. 2A). Specifically, M1A, M1B, and M1D exhibited similar cis-effects (χ2 test, all q > 0.098; Fig. 2A; Supplemental Table S3) but different trans-effects, with the three chromosomes falling into the order M1A > M1B > M1D in strength with respect to the numbers of dysregulated genes located on the unvaried chromosomes they induce via trans-regulation (χ2 test, all q < 0.008; Fig. 2A; Supplemental Table S3); this suggests that, although highly similar and syntenic among the three homeologous group 1 chromosomes, they have markedly variable trans-regulatory effects.
Third, although the two aneuploid strains concerning chromosome 2A (i.e. monosomic 2A [designated M2A, referring to loss of one chromosome 2A] and trisomic 2A [designated Tri2A, referring to gain of one extra chromosome 2A]) showed similar trends to M1A versus Tri1A (described above) in the sense that loss of a chromosome imposes a greater impact on gene expression than gain of the same chromosome (χ2 test, q = 0.016; Fig. 2A; Supplemental Table S4), the magnitude of difference between M2A and Tri2A with respect to the numbers of dysregulated genes (2,025 versus 1,738) was much smaller than that between M1A and Tri1A (2,262 versus 765; χ2 test, P = 2.60E-165; Fig. 2A), suggesting chromosome-specific effects.
Fourth, the two phenotypically compensated aneuploid strains (i.e. nullisomic 1A/trisomic 1B [designated N1ATri1B, referring to missing both chromosomes 1A and gaining a single chromosome 1B] and nullisomic 1A/tetrasomic 1B [designated N1AT1B, referring to missing both chromosomes 1A and gaining a pair of chromosomes 1B]) caused dysregulated expression of 1,730 genes (3.64%) and 2,136 genes (4.46%) relative to CS, respectively (Fig. 2A). Of the dysregulated genes, both those due to cis- and trans-effects are significantly different between the two strains (χ2 test, all q < 4.23E-17; Fig. 2A; Supplemental Table S5). However, the difference in the numbers of dysregulated genes between the two strains due to the trans-effect (N1ATri1B versus N1AT1B = 1,325:1,039) is much smaller than that due to the cis-effect (N1ATri1B versus N1AT1B = 405:1,097; χ2 test, P = 4.68E-70; Fig. 2A). This suggests that the extra 1B chromosome(s) added to the otherwise 1A nullisomy produced dual effects on dysregulated gene expression: on the one hand, it significantly attenuated the strong trans-effect caused by 1A nullisomy (Fig. 2A; Supplemental Fig. S2); on the other hand, it caused dysregulation of additional genes, primarily via a cis-effect, which scales with dosage (Fig. 2A). Taken together, these results suggest that (1) the cis-effect is largely chromosome dosage dependent irrespective of genomic environments harboring variable contents of homeologous chromosomes; and (2) to an extent, the effect of missing a pair of homologous chromosomes on dysregulated expression due to a trans-effect can be attenuated (manifested as a reduced number of dysregulated genes) by gaining one or a pair of its homeologous chromosome(s), which, however, appeared to be largely dosage insensitive. Again, we should caution that these characteristics may show chromosome or homeologous group specificity.
The differential impacts of the various types of aneuploidy on gene expression also were reflected by a hierarchical analysis of similarity in terms of overall expression patterns as well as their expression divergence from the common euploid CS (Fig. 2, B and C). The results showed that N1A is most divergent in overall expression patterns from the rest of the strains (Fig. 2, B and C). Most strikingly, the two compensated aneuploid strains, N1ATri1B and N1AT1B, are sister to N1A, and together, they formed a subcluster that is distantly related to the euploid CS and the other aneuploid strains (Fig. 2, B and C). This is unexpected, given that, based on phenotypic classification, these two strains are largely reverted to that of CS (Sears, 1944). However, this unexpected hierarchical pattern is consistent with the dual effects of adding one or a pair of homeologous chromosomes (1B) to the otherwise nullisomic strain (N1A), described above. Another unexpected result is that different types of aneuploid strains involving homeologous chromosomes (Tri1A and M1D) or even nonhomologous chromosomes (M1D and Tri2A) can be clustered together (Fig. 2B). This suggests that the effects of aneuploidy on dysregulated gene expression can be due primarily to the imbalanced chromosome content per se rather than to a gene-specific dosage effect. Similar findings were reported recently in a study in human pluripotent stem cells, which showed that chromosomally disparate aneuploidies generated highly similar global expression profiles that all contribute to a common phenotype, tumorigenicity (Ben-David et al., 2014).
With respect to the trans-effect, we further interrogated whether the expression of the three subgenomes, each as a whole, is similarly or differently impacted by the various types of whole-chromosome aneuploidy, and in particular, whether a given subgenome is more prone to transcriptional perturbation if one of its own chromosomes is in an aneusomic state than the intact subgenomes (harboring no aneuploid chromosome). We thus compared the pairwise differences between each two subgenomes for the total numbers of genes that showed dysregulated expression due to the trans-effect in a given aneuploid strain versus CS. The results showed that (1) in nine of the 10 aneuploid strains (except for M1B), subgenome B showed significantly more genes (Prop.test, all q < 0.029) manifesting trans-mediated dysregulation relative to CS than subgenome A (Table I); (2) in seven of the 10 aneuploid strains (except M2A, N1ATri1B, and N1AT1B), subgenome B showed significantly more genes (Prop.test, all q < 0.012) manifesting trans-mediated dysregulation relative to CS than subgenome D (Table I); and (3) in none of the10 aneuploid strains, subgenomes A and D showed a significant difference (Prop.test, all q > 0.071) with regard to the number of genes manifesting trans-mediated dysregulation relative to CS (Table I). Collectively, these results suggest that, with respect to the transcriptional response, of the three constituent subgenomes of hexaploid wheat, subgenome B is more sensitive to most types of the whole-chromosome aneuploidy we studied here than subgenomes A and D, while subgenomes A and D have similar degrees of response in all 10 aneuploid types studied. By extension, these results indicate that a given subgenome as a whole is not more prone to transcriptional perturbation when one of its own chromosomes was in an aneusomic state under the hexaploid wheat genomic environment.
Table I. Collective transcriptional responses by the subgenomes of hexaploid wheat to each of the 10 types of whole-chromosome aneuploidy.
A, B, and D refer to the three subgenomes of hexaploid wheat.
| Aneuploid Versus Euploid | ΣAa | ΣBa | ΣDa |
q Values (Prop.test)b |
||
|---|---|---|---|---|---|---|
| ΣA Versus ΣB | ΣD Versus ΣB | ΣA Versus ΣD | ||||
| N1A versus CS | 1,328 | 1,717 | 1,558 | 2.87E-02* | 4.15E-02* | 9.88E-01 |
| M1A versus CS | 357 | 744 | 431 | 6.14E-18*** | 2.68E-17*** | 9.09E-01 |
| Tri1A versus CS | 108 | 221 | 172 | 1.81E-05*** | 4.15E-02 * | 7.10E-02 |
| T1A versus CS | 422 | 620 | 513 | 1.60E-03** | 1.15E-02* | 9.09E-01 |
| M1B versus CS | 467 | 450 | 435 | 3.84E-01 | 4.16E-02* | 4.81E-01 |
| M1D versus CS | 181 | 235 | 162 | 2.87E-02* | 4.15E-02 * | 9.88E-01 |
| M2A versus CS | 366 | 532 | 461 | 2.87E-02* | 5.64E-02 | 9.09E-01 |
| Tri2A versus CS | 312 | 510 | 415 | 1.90E-04*** | 1.15E-02* | 4.96E-01 |
| N1ATri1B versus CS | 351 | 489 | 485 | 1.60E-04*** | 6.75E-02 | 7.10E-02 |
| N1AT1B versus CS | 284 | 357 | 398 | 2.87E-02* | 1.00E+00 | 7.10E-02 |
Sum of trans-effect genes belonging to a given subgenome, excluding genes residing on the aneusomic chromosome(s).
q values are adjusted P values from the Prop.test. Asterisks represent statistically significant differences between the pairwise comparisons: *q < 0.05, **q < 0.01, and ***q < 0.001.
Transcriptional Responses of the Normal Chromosomes to Aneuploidy Are Unequal, although There Is a Chromosome-Wide Even Distribution of Dysregulated Genes
The aforementioned results suggest that the three subgenomes of hexaploid wheat, when considered as a whole, are unequal in transcriptional responses to whole-chromosome aneuploidy, yet a given subgenome is not more responsive when one of its own chromosomes was in an aneusomic state than the intact subgenomes. Naturally, we asked whether this is due to a mass action of similar or differential responses by individual chromosomes (e.g. whether some chromosomes are intrinsically more responsive than others in all or most aneuploid strains). To address this question, we compared differences among the normal chromosomes with respect to their relative contributions to the total proportion of dysregulated genes due to the trans-effect of aneuploidy in a given aneuploid strain. Specifically, we tabulated the percentage of dysregulated genes (PDGs) in each normal chromosome against PDGs of the whole-genome average (excluding the aneusomic chromosomes) for each of the 10 whole-chromosome aneuploid strains studied (Supplemental Table S1) and calculated the statistical differences among the normal chromosomes for each strain. We found dramatic differences in PDGs among the normal chromosomes in each aneuploid strain, and some chromosomes are significantly more responsive than others in the majority of the aneuploid strains (Prop.test, q < 0.05; Fig. 3A). Taking all aneuploid strains together, it is apparent that chromosome 2B was most responsive (showing significantly higher PDGs than the whole-genome average in eight of the 10 aneuploid strains), followed by chromosomes 3B and 5B (exhibiting significantly higher PDGs in six of the 10 aneuploid strains), while chromosomes 2A, 6A, 6B, 2D, 4D, 5D, and 7D are the least responsive, which did not show higher than the whole-genome average PDGs in any of the aneuploid strains (Fig. 3A). Clearly, although all normal chromosomes in all 10 studied aneuploid strains showed dysregulated expression due to an aneuploidy-imposed trans-effect for a certain proportion of genes they encode, the clearly discernible differences among the chromosomes constituting each of the three subgenomes of hexaploid wheat can fully account for their overall similarity (A versus D) and differences (A versus B and B versus D) in transcriptional responses to whole-chromosome aneuploidy (Table I).
Figure 3.
Transcriptional responses to whole-chromosome aneuploidy by the different aneuploids. A, Heat map showing the q values (adjusted by false discovery rate [FDR]) of Prop.test between dysregulated genes in each normal chromosome against dysregulated genes of the whole-genome average (excluding the aneuploid chromosomes) for each aneuploid strain. The white, gray, and dark blue rectangles in each aneuploid strain denote the aneuploid chromosome(s), normal chromosomes on which the number of dysregulated genes did not transgress the whole-genome average, and normal chromosomes on which the number of dysregulated genes transgressed the whole-genome average, respectively. B, Distribution of genes showing dysregulated expression along each normal chromosome due to the transcriptional response in N1A. The red and blue dots represent up- and down-regulated genes, respectively. Results for the rest of the aneuploid strains are given in Supplemental Figure S3. C, Log2(fold change) of gene expression between N1A and CS along chromosomes 1B and 1D, depicted in gray. Red lines denote the smoothed distribution for the differentially expressed genes along the 1B and 1D chromosomes, as representatives, in N1A using the lowess function of R. The y axis represents the log2(fold change) of FPKM between N1A and its isogenic euploid (CS). The x axis represents the sorted positions of genes along the 1B and 1D chromosomes. Results of this analysis for all the normal chromosomes in each of the aneuploid strains are given in Supplemental Figure S4.
A further question to ask was whether regions along each normal chromosome would show equal or biased transcriptional responses to whole-chromosome aneuploidy. This question arises because it was shown in both human (trisomy 21, causation of Down syndrome) and mouse (segmental trisomy of chromosome 16) that genes due to trans-mediated dysregulation by aneuploidy are not distributed randomly along the normal chromosomes but clustered into coexpressed aggregates called gene expression dysregulation domains (GEDDs; Letourneau et al., 2014). Remarkably, similar alternating dysregulated expression also was observed in Brassica napus (Zhu et al., 2015), where, however, only aneuploidy for a single chromosome was studied. To interrogate whether this striking and unexpected gene expression pattern (Letourneau et al., 2014) also applies to the various aneuploid strains in the hexaploid genomic context of wheat, we analyzed the distribution of the dysregulated genes due to the trans-effect of whole-chromosome aneuploidy along each normal chromosome in each of the 10 aneuploid strains. We first plotted fold changes (log2 ratios) of all the aneuploidy versus CS differentially expressed genes (both up- and down-regulated) along all the normal chromosomes for a given aneuploid strain (Fig. 3B; Supplemental Fig. S3). The results indicated that the differentially expressed genes were mapped to the entire length of each normal chromosome in all 10 aneuploid strains we studied, consistent with prior studies in various organisms (Letourneau et al., 2014; Zhu et al., 2015). We then smoothed the distribution of fold changes (log2 ratios) for these differentially expressed genes along each normal chromosome for each aneuploid strain using the lowess function of R to identify potential GEDDs defined by the prior study (Letourneau et al., 2014). Surprisingly, this analysis showed that the dysregulated genes displayed a smooth distribution across the entire length of all the normal chromosomes in each of the 10 studied aneuploid strains of hexaploid wheat (Fig. 3C; Supplemental Fig. S4), indicating the absence of GEDDs in all the studied aneuploid strains of hexaploid wheat. To further verify this unexpected finding, we compared the percentages of dysregulated genes versus total expressed genes within each 1-Mb sliding window along each normal chromosome for each of the 10 aneuploid strains and calculated the statistical difference for each window using binomial distribution. We found that only two chromosomal regions (i.e. a terminal region of the long arm of chromosome 2B and a proximal-terminal region of the long arm of chromosome 7A; Supplemental Table S6) showed significantly higher proportions of dysregulated expression than the whole-genome average (q < 0.05), suggesting a lack of a regional hotspot of dysregulated gene expression due to the trans-effect of whole-chromosome aneuploidy in hexaploid wheat. Together, our results indicate that, in contrast to the findings in human, mouse (Letourneau et al., 2014), and probably B. napus (Zhu et al., 2015), genes showing transcriptional responses to whole-chromosome aneuploidy in hexaploid wheat are not aggregated to GEDDs.
Widespread Dosage Compensation Likely Exists in Hexaploid Wheat
Aneuploidy not only produces dosage effects (cis-effects) and its attendant downstream genome-wide transcriptional responses (trans-effects) but also can elicit dosage compensation for genes residing on the aneuploid chromosome(s), whereby the wild-type euploid gene expression level is robustly maintained irrespective of copy number changes. Although dosage compensation is known to widely exist in animal sex chromosomes and autosomes of some species, such as Drosophila spp. (Sun et al., 2013a, 2013b), the occurrence of dosage compensation in autosomes of other organisms (e.g. yeast), as well as the extents of the phenomenon in different organisms, remain contentious (Torres et al., 2016). Previous studies in plants indicated that, whereas dosage compensation is prominent in maize (Zea mays; Birchler, 1979; Guo et al., 1996), it occurred only moderately in Arabidopsis (Henry et al., 2007; Huettel et al., 2008). Our observation indicated that less than 30% of the expressed genes residing on a given aneuploid chromosome in all 10 studied whole-chromosome aneuploid strains showed altered expression due to a dosage effect (Supplemental Table S7). This striking robustness in gene expression to chromosome-wide dosage alteration strongly indicates the presence of dosage compensation in all chromosomes of hexaploid wheat. To test this possibility, we took advantage of two sets of aneuploid strains each with grading dosages of one particular chromosome in the common euploid background of CS (Supplemental Table S1). We performed stringent statistical filtrations for genes that (1) were encoded exclusively by the numerically altered chromosome (the aneuploid chromosome) and (2) showed highly constant expression levels in all the relevant strains with a dosage gradient for the pertinent chromosome. Specifically, the aneuploid strains used for this analysis included M1A (one copy of 1A), euploid CS (two copies of 1A), Tri1A (three copies of 1A), T1A (four copies of 1A), M2A (one copy of 2A), euploid CS (two copies of 2A), and Tri2A (three copies of 2A). Based on the highly stringent filtering (detailed in “Materials and Methods”), we identified 254 and 378 genes exhibiting clear dosage compensation in chromosomes 1A and 2A, respectively, which accounted for 12% to 14% of all the expressed genes (aneuploid versus euploid CS) located on the respective aneuploid chromosomes (Fig. 4A; Supplemental Fig. S6A). We further assessed the distribution of these genes on the aneuploid chromosomes against the theoretical distribution (Torres et al., 2016). We observed a left-skewed distribution in both Tri1A and T1A (expected value > median > mean, skewness = −0.45 and −0.25; Fig. 4C; Supplemental Fig. S5) and a right-skewed distribution in M1A (expected value < median < mean, skewness = 0.31) in otherwise typical normal distributions (Fig. 4B). Similar situations were observed for chromosomes M2A and Tri2A (Supplemental Fig. S6, B and C). Furthermore, we quantified the relative distribution frequencies of fold changes in expression in each of these five aneuploid strains concerning chromosome 1A or 2A versus CS. We found that genes showing a dosage effect and genes showing dosage compensation manifested distinct distributions with little overlapping (Supplemental Fig. S7). Altogether, our data clearly show the existence of widespread dosage compensation in hexaploid wheat.
Figure 4.
Dosage compensation for genes located on numerically altered chromosome 1A. A, Box plot showing the distribution of FPKM values for genes along chromosome 1A, with scaled dosage of the chromosome from 1 to 4. The red dashed line represents the expected dosage effect of chromosome 1A if no dosage compensation occurs, while the green dashed line shows the observed median of gene expression in the euploid (CS). B, Frequency distribution of log2(fold change) in M1A (relative to the euploid CS). Log2(fold change) of 0.1 is the bin size in the histogram. The gray line represents the expected value if no dosage compensation occurs, while the blue and red lines are the observed median and mean of distribution, respectively. C, Frequency distribution of log2(fold change) in Tri1A (relative to the euploid CS). Denotations for the gray, blue, and red lines are as for B. The values of mean, median, and skewness are shown.
Genes Showing Dosage Effects, Dosage Compensation, and Transcriptional Responses Are Enriched for Distinct Functional Categories
The foregoing results indicated that three broad types of dysregulated expression are associated with whole-chromosome aneuploidy in hexaploid wheat: dosage effects (dysregulated genes mapped to the aneuploid chromosomes due to a dosage-mediated cis-effect), dosage compensation (robust euploid-level expression of genes mapped to the aneuploid chromosomes irrespective of dosage alteration), and transcriptional responses (dysregulated genes residing on the unvaried chromosomes of a given aneuploid strain due to a trans-acting effect). It is of apparent interest to inquire whether these different gene groups under distinct regulatory mechanisms would bear different biological consequences. To test this, we performed a Gene Ontology (GO) analysis for each of the gene groups identified in the diverse whole-chromosome aneuploid strains of hexaploid wheat. First, we analyzed the two distinct sets of genes mapped to the aneuploid chromosome(s) of the relevant aneuploid strains (Supplemental Table S1), which showed either a dosage effect or dosage compensation in a given aneuploid strain. We found that genes showing a dosage effect were significantly enriched for annotated GO terms involved in signal transduction, response to stress, and those associated with the nucleus, while genes showing dosage compensation were overrepresented by GO terms associated with cell wall macromolecule metabolism, peptidoglycan biosynthesis, and ribosome (Fig. 5A; all q < 0.014, based on hypergeometric distribution). It is thus clear that genes showing dosage effects or dosage compensation in the whole-chromosome aneuploid strains of hexaploid wheat were enriched for distinct annotated GO terms, with the former involved mainly in signal transduction and response to stress while the latter were involved mainly in growth and cellular metabolism.
Figure 5.
Distinct GO enrichments for genes mapped to aneuploid chromosomes, which showed dosage compensation or dosage effects, and for genes mapped to the unvaried chromosomes, which showed transcriptional responses. A, Significantly overrepresented GO terms by genes mapping to chromosome 1A or 2A, which showed either dosage effects or dosage compensation in the relevant aneuploid strains, with graded dosage alterations from 1 to 4 and 1 to 3 for chromosomes 1A and 2A, respectively. B, The q values of enriched GO categories for genes showing direct or inverse trans-effects in all 10 aneuploid strains. The x axis represents the log10(q). The dashed line represents the cutoff q value of 0.05 [log10(0.05) = 1.3].
Next, we conducted GO analysis for genes residing on normal chromosomes in each of the 10 aneuploid strains separately that showed transcriptional responses. Depending on the directionality of responses (i.e. positive versus negative) to the varied aneuploid chromosome dosage, genes showing transcriptional responses can be divided further into direct trans-effect and inverse trans-effect, respectively (Birchler, 1981, 2012; Guo and Birchler, 1994). We found that (1) genes manifesting a direct trans-effect in most of the 10 aneuploid strains were overrepresented by GO terms involved in responses to oxidation and stimulus, carbohydrate metabolism, and cell wall biogenesis [Fig. 5B; log10(q) > 1.3]; (2) genes manifesting an inverse trans-effect in most aneuploid strains showed enriched GO terms involved in photosynthesis, transcription, regulation of RNA metabolism, and protein metabolism [Fig. 5B; log10(q) > 1.3]; and (3) genes manifesting an inverse trans-effect in the two aneuploid strains with loss of one or both chromosomes 1A (M1A and N1A) were enriched for GO terms involved in ribosome biogenesis [Fig. 5B; log10(q) > 1.3]. In addition, an analysis of GO terms in the molecular function category also identified distinctly enriched functional gene groups. For example, transporter activity and oxidoreductase activity were significantly overrepresented by genes manifesting a direct trans-effect in most or all 10 aneuploid strains, while functional gene groups related to transcription regulator activity, transcription factor activity, and DNA binding were significantly enriched by genes manifesting an inverse trans-effect in some aneuploid strains [Supplemental Fig. S8; log10(q) > 1.3]. Taken together, these results indicated that genes showing transcriptional responses are involved in diverse functional gene groups and cellular pathways, as expected given that all normal chromosomes of a given aneuploid strain are affected (Fig. 2; Table I). Nevertheless, genes with contrasting directionality of responses (direct versus inverse) to dose alteration of an unrelated chromosome(s) are signified by distinct functional GO terms.
Homeologous Genes in Hexaploid Wheat Are Rarely Coregulated in Response to Whole-Chromosome Aneuploidy
The foregoing analyses are all based on the total expressed genes. Given the allohexaploid nature of common wheat, an interesting issue concerning the transcriptional responses to aneuploidy is how the expression of those genes that are encoded by the homeologous chromosomes of a given chromosome group, which are homeologous and syntenic with the numerically altered chromosome, would respond. To address this issue, we first focused on a set of chromosome group 1 homeolog-specific genes in hexaploid wheat that had exactly one copy in chromosomes 1A, 1B, and 1D and that were defined as triplet genes (Pfeifer et al., 2014). This set of triplet genes can be reliably distinguished by diagnostic single-nucleotide polymorphisms based on the wheat (CS) reference genome sequence (Pfeifer et al., 2014). We compared the expression levels (log2 ratio) for each member within a given triplet gene between each of the three homeologous group 1 monosomics (M1A, M1B, and M1D) versus their common isogenic euploid CS and identified the differentially expressed triplets in each of the comparisons. The results showed that, in M1A, the expression levels of chromosome 1A homeologs for this set of triplets exhibited a large reduction relative to those of CS (Z statistic = −2.6288, P = 0.00428; detailed in “Materials and Methods”), while the 1B homeologs (Z statistic = −0.1952, P = 0.4226) and 1D homeologs (Z statistic = −0.3267, P = 0.3719) did not show discernible changes in expression relative to their counterparts in CS (Fig. 6A). We also quantified contributions by the three homeologs to each of the differentially expressed triplets between M1A and CS by an UpSet plot (Fig. 6B), whereby their respective contributions to each of these differentially expressed triplets can be classified into nine patterns. The most prominent pattern is direct down-regulation of chromosome 1A homeologs (due to the cis-effect), which included 402 triplets (91.4% of the total 438), with the remaining 36 triplets showing trans-effect-mediated coordinated changes between two homeologs or among all three homeologs (Fig. 6B). We observed the same trend in M1B and M1D (Fig. 6, C–F). In the two phenotypically compensated aneuploid strains (N1ATri1B and N1AT1B), we also observed little evidence of interactions between subgenomes B and D, with the major changes in both strains being confined to direct up-regulation of the 1B homeologs due to the cis-effect that scales with the 1B chromosome dosage (Supplemental Fig. S9). Next, we conducted an independent hierarchical clustering analysis for this set of homeologous group 1 triplet genes in the three homeologous group 1 monosomics (M1A, M1B, and M1D) and their common isogenic euploid CS. We found that the expression patterns of this set of triplet genes were separated by subgenomes rather than by genotypes (Supplemental Fig. S10). Taken together, it can be concluded that, albeit highly similar and syntenic, the homeologous chromosomes of hexaploid wheat did not show a compensating effect by up-regulating the expression of the homeologous genes when the homologous chromosome pair of one subgenome was missing. In other words, homeologous chromosomes were not more responsive than nonhomologous chromosomes regarding transcriptional responses to whole-chromosome aneuploidy in hexaploid wheat.
Figure 6.
Expression of homeologous members in a set of chromosome group 1-specific triplet genes in the same type of whole-chromosome aneuploidy (monosomics of 1A, 1B, and 1D) of hexaploid wheat. A, C, and E, Distributions of differentially expressed triplets [log2(fold change)] relative to euploid CS in M1A (A), M1B (C), and M1D (E). The values of the Z statistic and the corresponding P values are shown at the bottom of each graph. P values labeled with asterisks refer to significant difference at P < 0.01 (**) and P < 0.001 (***). B, D, and F, UpSet plots showing the detected expression patterns among the triplet members in M1A (B), M1B (D), and M1D (F). The black dots at the bottom of the vertical bars indicate the expressed triplet members, with the total triplet gene numbers of each pattern shown at the top of the vertical bars. Horizontal bars on the left denote the directions of the expression changes (up- or down-regulation, relative to euploid CS) by the triplet gene numbers in each situation.
Given the unexpected nature of this observation, we conducted an independent analysis of all 10 aneuploid strains using locus-specific cDNA pyrosequencing for a subset of nine homeologous group 1 triple genes that showed differential expression that was in line with chromosome dosage as well as met the stringent criteria for designing the pyrosequencing primers (Zhang et al., 2013a). We compared the data with those from the corresponding RNA-seq reads and found that, in all nine studied triplet genes, the two sets of data were fully concordant (Supplemental Fig. S11, A–I), thus validating the reliability of our RNA-seq data and analysis. Specifically, the pyrosequencing data revealed that the expression change by a member of a given triplet is highly proportionate to the dosage of the chromosome(s) in question, with no evidence for coordinated expression changes by its homeologs (Supplemental Fig. S11, A–I). In addition, we also included three homeologous group 2 triplet genes for the pyrosequencing analysis. We observed similar results to those of the group 1 triplet genes, in that the RNA-seq data can be fully validated by this independent analysis (Supplemental Fig. S11, J–L). Once again, we should caution that, although two homeologous chromosome groups (1 and 2) were studied here, the possibility remains that the unvaried chromosome groups may not show exactly the same trend, which requires further investigations.
Phenotypic Consequences of Whole-Chromosome Aneuploidy in Hexaploid Wheat
The genomically imbalanced nature of whole-chromosome aneuploidy often has severe phenotypic consequences in all organisms studied (Williams and Amon, 2009; Henry et al., 2010; Birchler, 2014). Although many types of aneuploidy in plants are viable and fertile, they manifest pleiotropic developmental defects and generally impaired fitness. For example, in maize and Arabidopsis, the abnormal phenotypes caused by aneuploidy include developmental defects, partial sterility, alterations in plant architecture, and so forth (Birchler et al., 2001; Birchler and Veitia, 2007; Makarevitch et al., 2008; Henry et al., 2010). Qualitatively, hexaploid common wheat is no exception to this general rule. Indeed, the seminal work by E.R. Sears many decades ago has already established that whole-chromosome aneuploidy in the standard genotype (CS) of common wheat is associated with an array of abnormal phenotypes (Sears, 1944). Here, we compared several typical phenotypic traits between the aneuploid strains and their isogenic euploid CS in order to get some insights into the relationship between the degrees of dysregulated genes and severity in phenotypic abnormality. The phenotypic traits assessed include fresh weight of seedlings, plant height, tiller number, spikelet density, spike length, spikelet number, and seed setting. Prior studies in yeast have established that there are two broad types of phenotypes associated with aneuploidy: one is gene-specific phenotypic variations observable only in specific aneuploid strains, and the other is general phenotypic abnormality manifested by all or most types of aneuploidy irrespective of the aneuploid chromosomes (Dodgson et al., 2016). We also observed both types of abnormal phenotypes in the hexaploid wheat aneuploid strains. For example, plant height and seed setting (a reflection of reproductive fitness) were reduced significantly in all aneuploid strains, with N1A being mostly impaired (Fig. 7, A and C). Some phenotypic traits were affected significantly (Student’s t test, P < 0.05) in only some of the aneuploid strains but not in others, such as seedling fresh weight and tiller number (Supplemental Fig. S12, A and B). Moreover, some traits were impacted in opposite directions in the different aneuploid strains, such as spikelet density and spike length (Fig. 7, B and D). The severity of some phenotypes clearly scales with the numerically varied chromosome dosage. For example, a negative correlation between the dosage of chromosome 1A and spikelet density was apparent in aneuploid strains M1A, Tri1A, and T1A and euploid CS (Fig. 7, B and E). Specifically, compared with CS, the distances between spikelets were increased in M1A but decreased in Tri1A and T1A (Fig. 7, B and D; Supplemental Fig. S12C). Interestingly, the phenotypes of M1B and M1D for this trait were similar to M1A, while M2A did not show this phenotypic change, suggesting that genes controlling the density of spikelets are encoded by the homeologous group 1 chromosomes (1A, 1B, and 1D) in hexaploid wheat. Notably, the similar and differential alterations to the multiple component traits related to the overall spike morphology have accumulated significant variations of this complex trait among the aneuploid strains (Fig. 7E). The two compensating aneuploid strains (N1ATri1B and N1AT1B) showed clear, but only partial, attenuating effects of the adverse phenotypic impacts of N1A in all traits quantified (Fig. 7; Supplemental Fig. S12), consistent with the original report (Sears, 1944).
Figure 7.
Variation in typical phenotypic traits in the whole-chromosome aneuploid strains relative to their isogenic euploid wild type (CS) of hexaploid wheat. A to D show quantitatively tabulated values of plant height, spikelet density, seed setting, and spike length, while E is an image showing the overall morphology of spikes. Asterisks denote statistical significance in the aneuploid versus euploid (CS) pairwise comparisons based on Student’s t test: *, P < 0.05; **, P < 0.01; and ***, P < 0.001. Bar in E = 1 cm.
DISCUSSION
Aneuploidy, in which the copy number of one or more chromosomes deviates from the balanced multiple of a haploid complement, represents a large-effect mutation that gravely affects cellular physiology and has profound phenotypic consequences (Torres et al., 2008; Birchler and Veitia, 2012; Dodgson et al., 2016; Rutledge and Cimini, 2016). Apparently, all biological consequences of aneuploidy are rooted in dosage effects of genes encoded by the numerically altered chromosome(s); nevertheless, the mechanisms whereby a specific end phenotypic manifestation being brought about by aneuploidy can be due to indirect effects of the numerically altered chromosome(s) and, hence, can be extremely complex. Since the first unequivocal documentation of trans-acting effects of aneuploidy on gene expression in maize (Guo and Birchler, 1994), it has been generally recognized in diverse cellular and organismal systems that the expression-altered genes due to aneuploidy are not restricted to those located on the aneusomic chromosome(s) but include a sizable fraction of genes residing on all the unvaried chromosomes, a phenomenon collectively termed aneuploidy-induced transcriptional response (Sheltzer et al., 2012). Therefore, physiological and phenotypic consequences of aneuploidy can be either attributable directly to the altered expression of genes encoded by the aneusomic chromosome(s) due to a dosage effect (i.e. cis-effect) or indirectly to expression changes of many genes encoded by the unvaried chromosomes (i.e. trans-effect), which generate additive or synergistic expressional and functional effects and which, in turn, may interact with the dosage-altered genes at the transcriptional and/or posttranscriptional levels (Pavelka et al., 2010). This is consistent with the nonlinear nature of gene dosage effects and their downstream biochemical processes (Veitia et al., 2013; Pires and Conant, 2016). Consequently, most if not all aneuploidy-induced biological effects can be accounted for by the gene dosage balance hypothesis at genome-wide scales (Birchler and Veitia, 2012; Veitia and Potier, 2015).
The seminal work by E.R. Sears in the early 1900s has already established that hexaploid wheat possesses a greater buffering capacity against the adverse effects of many types of whole-chromosome aneuploidy and, hence, fostered the generation and persistence of a diverse repertoire of various aneuploid strains that, in most cases, include all 21 chromosomes (Sears, 1944). Nevertheless, the molecular basis for the hexaploid wheat’s remarkable ability to tolerate aneuploidy has not been explored. A straightforward molecular metaphor conceivable for the phenomenon apparently lies in the nature of hexaploidy per se. However, this metaphor would entail a default assumption that the homeologous chromosomes can compensate for each other at the gene expression level. Our results, by clearly showing that the homeologous chromosomes are not more responsive to missing a copy of the group 1 homeologous chromosomes (i.e. monosomics for 1A, 1B, and 1D) than nonhomologous chromosomes with respect to trans-acting effects, strongly argue against this metaphor. Instead, we propose that the remarkable aneuploidy-tolerating capacity of hexaploid wheat is more likely due to its intrinsically stronger phenotypic robustness (hence, maintenance of fitness) to perturbed gene expression. Our observations that (1) all 10 diverse types of whole-chromosome aneuploidy we studied have induced significantly dysregulated expression of a sizable proportion of the expressed genes and (2) the two phenotypically compensated aneuploid strains (i.e. N1ATri1B and N1AT1B) showed no smaller proportions of dysregulated genes than most of the phenotypically altered aneuploid strains have lent strong support to the possibility we proposed above.
A notable observation is the substantial differences among the normal chromosomes in their responses to a given whole-chromosome aneuploidy, which have accumulated to marked differential responses by the three subgenomes, with subgenome B being significantly more responsive than subgenomes A and D. This is consistent with the findings that the three subgenomes of hexaploid wheat are asymmetric at both structural and expression levels (Feldman et al., 2012; Pont et al., 2013) and are functionally partitioned across development or under different environmental conditions (Pfeifer et al., 2014; Yang et al., 2014). Notably, subgenome expression asymmetry in polyploid wheat is already evident at the onset of allopolyploidization, which showed further augmentation in the course of evolution and domestication at both the tetraploid and hexaploid levels (Wang et al., 2016). According to the pivotal-differential genome hypothesis for polyploid wheat evolution, subgenome A is considered the most fundamental subgenome (pivotal) to polyploid wheat because it controls essential biological attributes, while subgenome B is more plastic and mainly confers adaptation to biotic and abiotic stresses (Feldman et al., 2012; El Baidouri et al., 2017; Mirzaghaderi and Mason, 2017). This notion broadly accords with our results showing that subgenome B is more responsive than subgenome A to unbalanced karyotypes of whole-chromosome aneuploidy.
An interesting discovery reported recently in human monozygotic twins discordant for trisomy 21 (the genetic underpinning of Down syndrome) is that differential expression between the twins is organized in clustered aggregates along all chromosomes, a pattern dubbed GEDDs (Letourneau et al., 2014). Importantly, similar expression patterns also were observed in induced pluripotent stem cells from the diseased twin harboring trisomy 21, in mouse with segmental trisomy of chromosome 16 (Letourneau et al., 2014), and, remarkably, in aneuploidy (monosomics) of a plant species, B. napus (Zhu et al., 2015). Thus, our exhaustive analysis documenting that the GEDD pattern does not exist in any of the 10 aneuploid strains (including chromosome gain or loss) of hexaploid wheat came as a surprise. It was suggested that the occurrence of the GEDD pattern could be attributed to a reduced dynamics of gene expression in the trisomics (Letourneau et al., 2014). Thus, the absence of GEDDs in aneuploidy of wheat may suggest a higher degree of robustness of its allohexaploid genome in maintaining gene expression dynamics and uncompromised fine-tuning of gene expression even in cases of strong genetic perturbation by whole-chromosome aneuploidy. This is consistent with the remarkable genomic plasticity characteristic of hexaploid wheat, an attribute deemed critical to its evolutionary success as a species and its broad adaptation to diverse environments as an outstanding major crop (Dubcovsky and Dvorak, 2007). We anticipate that further exploration into this issue may generate novel insights into the unique features of allopolyploidy in response to severe genetic perturbations of unbalanced karyotypes. That only negligible fitness loss was observable in diverse types of aneuploidy associated with nascent allohexaploid wheats further corroborates this possibility (Zhang et al., 2013b). Our argument that a strong robustness to genetic perturbation must be an essential property of hexaploid wheat also is based on another path of reasoning: the repeated genetic admixture and introgression from both of its tetraploid (tetraploid wheat [Triticum turgidum], genome BBAA) and diploid (goat grass [A. tauschii], genome DD) progenitors in the course of its domestication and global dispersal (Dubcovsky and Dvorak, 2007; Matsuoka, 2011; Wang et al., 2013). These repeated interploidy hybridization events have been suggested as essential to account for the rich genetic diversity seen in the current genetic pools of hexaploid wheat, which has undergone a strong genetic bottleneck of speciation via allopolyploidy only approximately 8,500 years ago (Dubcovsky and Dvorak, 2007; Matsuoka, 2011; Wang et al., 2013). The fact that hexaploid wheat, both as a species and a crop, has not only survived these traumatic genomic imbalances (anisoploidy and aneuploidy) but also prospered from them lends further support to its intrinsic robustness against genetic disturbance.
Complex dosage compensation mechanisms are known to have evolved in diverse organisms, including both plants and animals, which attenuate the adverse effects of dosage imbalance (Birchler and Veitia, 2012; Sun et al., 2013a, 2013b; Veitia et al., 2013; Pires and Conant, 2016). However, the scope and efficiency of dosage compensation vary markedly across organisms and even between different ecotypes of a given species (Hose et al., 2015). Here, we show that no more than 30% of the expressed genes residing on the various aneuploid chromosomes of hexaploid wheat showed altered expression compared with their isogenic euploid counterparts. Detailed analysis of the distribution of a set of expression-robust genes residing on the two aneuploid chromosomes (1A and 2A), for which the aneusomic chromosome dosage varied in gradient, revealed a canonical pattern of dosage-compensated genes (Torres et al., 2016). Thus, possessing efficient dosage compensation mechanisms is likely another property of the hexaploid wheat genome, which counteracts the dosage effect for a large number of dosage-altered genes and, hence, provides an efficient mechanism to attenuate the adverse effects of genetic disturbance like whole-chromosome aneuploidy on cellular physiology and phenotype.
Extensive studies in yeast have documented that there are two broad categories of phenotypes associated with aneuploidy: chromosome-specific phenotypes unique to the pertinent chromosome being numerically altered and a set of general phenotypes shared by many kinds of aneuploidy irrespective of the aneusomic chromosome (Torres et al., 2007; Sheltzer et al., 2011; Dodgson et al., 2016). While the chromosome-specific phenotypes are often caused by misexpression of one or a few large-effect dosage-sensitive genes mapped to the aneusomic chromosome, the general phenotypes common to different types of aneuploidy are due mainly to the mass effects of misexpression of many individual minor-effect genes residing on the normal chromosomes (Bonney et al., 2015). The most prominent general phenotypes of aneuploidy are defect in cellular proliferation and retardation in growth due to misexpression of a large number of genes involved in cell division and the cell cycle as a result of transcriptional responses induced by many types of aneuploidy (Sheltzer et al., 2012). In Arabidopsis, aneuploidy is associated with a plethora of impaired developmental phenotypes (Henry et al., 2010), as expected for a higher plant in which developmental patterning is controlled by complex and intricate gene regulatory networks that are especially sensitive to perturbed gene expression (Tang and Amon, 2013). Here, we show that both types of abnormal phenotypes also are associated with the aneuploid strains in hexaploid wheat and that the severity of both types of phenotypes largely scale with the degree of aneuploidy or the severity of genomic imbalance. This suggests that the degree of dysregulated gene expression due to both dosage effect (cis-effect) and transcriptional response (trans-effect) is positively associated with the degree of phenotypic abnormality in the aneuploid strains. However, the exact molecular mechanism underlying a specific trait can be disparate: some traits can be due to misexpression of a single large-effect gene, while others can be the cumulating effect of many dysregulated genes, the individual effects of which are cryptic (Tang and Amon, 2013). The diverse enriched GO terms for the dysregulated genes corroborate the latter possibility. Notably, partial restoration toward normal phenotypes is observable in the two compensating aneuploid strains, N1ATri1B and N1AT1B, as originally discovered by E.R. Sears (Sears, 1944). However, as discussed above, this tinkering toward phenotypic normalcy is not brought about by reduced numbers of genes that are dysregulated, since most of the phenotypically abnormal strains (e.g. Tri1A and M1D) exhibited much lower numbers of dysregulated genes. Thus, the molecular underpinnings of phenotypic compensation in these compensated plants must act at the protein or more downstream level, an issue that warrants further investigation.
To conclude, to our knowledge for the first time, we have systemically investigated the impact of whole-chromosome aneuploidy on transcriptome-level gene expression in hexaploid wheat. Compared with prior studies mainly concerning diploid or haploid genomes, we have unraveled novel features of chromosome-, subgenome-, and genome-wide gene expression alterations associated with the diverse types of aneuploidy in an important allopolyploid genome that constitutes one of the most important agricultural crops that humans have ever domesticated. Our findings have added new insights toward deeper understanding of an allopolyploid genome with respect to its gene regulatory and functional interplay and its phenotypic manifestation, which bears significance in the context of polyploidy, a ubiquitous and cyclic event associated with the evolutionary history of all higher plants (Doyle et al., 2008; Van de Peer et al., 2009; Jiao et al., 2011). Our results also may have implications in the translational aspect of functional genomics studies with respect to creating novel crops via hybridization and polyploidization (Mason and Batley, 2015).
MATERIALS AND METHODS
Plant Materials
A total of 10 whole-chromosome aneuploid strains, all in the common genetic background of the standard laboratory genotype CS of hexaploid wheat (Triticum aestivum; genome BBAADD, 2n = 6x = 42), were used in this study. The aneuploid strains were as follows: (1) nullisomic 1A (missing a pair of chromosomes 1A, designated as N1A, 2n = 40); (2) monosomic 1A (missing one chromosome 1A, designated as M1A, 2n = 41); (3) monosomic 1B (missing one chromosome 1B, designated as M1B, 2n = 41); (4) monosomic 1D (missing one chromosome 1D, designated as M1D, 2n = 41); (5) monosomic 2A (missing one chromosome 2A, designated as M2A, 2n = 41); (6) trisomic 1A (gaining one chromosome 1A, designated as Tri1A, 2n = 43); (7) trisomic 2A (gaining one chromosome 2A, designated as Tri2A, 2n = 43); (8) tetrasomic 1A (adding a pair of chromosomes 1A, designated as T1A, 2n = 44); (9) nullisomic 1A/trisomic 1B (missing a pair of chromosomes 1A and gaining one chromosome 1B, designated as N1ATri1B, 2n = 41); and (10) nullisomic 1A/tetrasomic 1B (missing a pair of chromosomes 1A and gaining a pair of chromosomes 1B, designated as N1AT1B, 2n = 42; Supplemental Table S1). All plants were grown in a common growth chamber under controlled conditions (day/night, 22°C/16°C, 16/8 h). When the third leaf appeared and the second leaf fully expanded (Simmons et al., 1985), the second leaf of each of the 10 aneuploid strains and the euploid CS was collected for RNA isolation. At this developmental stage, all 10 aneuploid strains and the euploid CS are phenotypically identical (Supplemental Fig. S13). All collected leaves were kept at −80°C until use.
Karyotyping
GISH and FISH were combined in sequence to identify the karyotypes of every individual plant for each aneuploid strain (Supplemental Table S1) and their CS euploid wild type before sampling the tissues. The protocols were largely as described originally (Han et al., 2004; Kato et al., 2004), with minor modifications (Zhang et al., 2013b). Each of the FISH and GISH images was acquired using an epifluorescence Olympus BX61 microscope and processed with Adobe Photoshop CS 5.0 in its entirety (Supplemental Fig. S1).
Transcriptome Sequencing
Total RNAs were isolated from the frozen tissues using Trizol reagent (Invitrogen) according to the manufacturer’s instructions. The integrity, quality, and concentration of extracted RNAs were assessed with the Agilent 2100 Bioanalyzer (Agilent Technologies). Transcriptome libraries were constructed for each sample and sequenced using the Illumina HiSeq 2000 platform with standard protocols. Two biological replications were used for each of the aneuploid strains (Supplemental Table S1) as well as their common euploid wild type (CS) and sequenced as parallel experiments. Low-quality reads (20% of bases with PHRED scores less than 20) were filtered from the raw data by using the FASTX-Toolkit (-p 80 -q 20; http://hannonlab.cshl.edu/fastx_toolkit). In total, approximately 212-Gb high-quality paired-end reads (100 bp) were obtained from 22 libraries (Supplemental Fig. S14A).
Read Alignment and RNA-Seq Data Analysis
The hexaploid wheat (CS) genome sequence and its annotation information were downloaded from Ensembl Plants (http://plants.ensembl.org/Triticum_aestivum). Then, each set of cleaned data was aligned to the reference using TopHat (version 2.0.11) with the following parameters: read-mismatches 2, segment mismatches 1, max-multihits 20, -r 0 (International Wheat Genome Sequencing Consortium, 2014). The raw data information and mapping efficiency are shown in Supplemental Figure S14 and Supplemental Table S9. The uniquely mapped reads to the reference sequence were computed. The assessment of transcriptome size was conducted according to the method reported (Coate and Doyle, 2010; Matos et al., 2015). The differentially expressed genes were determined by using Cuffdiff (version 2.2.1) through comparing the FPKM values. Transcripts with an FDR-adjusted (Benjamini and Hochberg, 1995) P < 0.05 were considered to exhibit statistically significant expression differences between samples. Given the widespread transcriptional responses of aneuploidy (Sheltzer et al., 2012; Birchler, 2014; Dürrbaum and Storchová, 2016), we did not normalize the expression data using genes residing on the unvaried chromosomes, as cautioned (Birchler, 2010, 2014). GO enrichment analysis was performed by hypergeometric distribution in R, with an adjusted P < 0.05 as a cutoff to determine significantly enriched GO terms. We downloaded the wheat GO annotation file from the agriGO Web site (http://bioinfo.cau.edu.cn/agriGO/; Du et al., 2010).
Analysis of Dosage Compensation
We used data concerning two chromosomes to interrogate the occurrence of dosage compensation in hexaploid wheat, which included chromosome 1A (with dosage gradient from 1 to 4; i.e. M1A, CS, Tri1A, and T1A) and chromosome 2A (with dosage gradient from 1 to 3; i.e. M2A, CS, and Tri2A). Candidate genes for which dosage compensation might have occurred were selected by a strict three-step filtration. First, we excluded the dysregulated genes (differentially expressed genes) in the pairwise comparisons between each aneuploid strain versus the euploid wild type. After this step, we identified 995 nondifferentially expressed genes residing on chromosome 1A from the M1A versus CS, Tri1A versus CS, and T1A versus CS pairwise comparisons and 1,285 nondifferentially expressed genes residing on chromosome 2A from the M2A versus CS and Tri2A versus CS pairwise comparisons. Second, a correlation test (Pearson correlation coefficient) between the expression level and the scaled-up dosage variation for each gene was performed according to the method described (Shi et al., 2015). If the correlation coefficient was significant for a given gene (FDR-adjusted P < 0.05), then it was removed from the candidate gene list. Third, one-way ANOVA was used to determine whether there was any statistically significant difference in expression between two or more samples within the 1A or 2A chromosome group. Then, Tukey’s honestly significant difference test was used to determine the specific genes that showed significant expression differences in any of the pairwise comparisons within the 1A or 2A chromosome group. In both of these tests, a false discovery value below 0.05 was excluded. Finally, the still remaining genes were considered as dosage compensated in the aneuploid strains; that is, these genes showed a robust wild-type-level expression irrespective of dosage.
Selection of Homeologous Genes
Homeologous genes were defined as triplets that represent strictly unigenes shared among the A, B, and D subgenomes of hexaploid wheat (International Wheat Genome Sequencing Consortium, 2014). A total of 8,605 triplets were downloaded from the wheat genome sequence repertoire (released by the International Wheat Genome Sequencing Consortium). Differentially expressed triplets were defined if at least one of the three members exhibited significant differential expression in the aneuploid versus euploid comparisons. To assess the transcriptional response by each subgenome to the whole-chromosome aneuploidy, the triplets that showed altered expression in each of the aneuploid versus euploid comparisons were presented as dot plots using the ggplot2 package in R. The relative quantitative contribution by each subgenome to the total expression level of a given triplet was visualized by an UpSet plot (Lex et al., 2014). In addition, a hierarchical clustering of the expressed triplets mapping to the homeologous group 1 chromosomes was conducted using the pvclust function implemented in R with correlation distance for log2(FPKM+1) transformed expression values and clustering by the average method.
Subgenome-Specific cDNA Pyrosequencing
The protocol essentially followed the original report (Mochida et al., 2003) with modifications (Zhang et al., 2013a). A set of differentially expressed triplets based on the transcriptome profiling results was arbitrarily selected to design the pyrosequencing primers for the purpose of assaying subgenome-specific expression by the pyrosequencing system (PyroMarkID Q96; Qiagen). The SeqMan program (http://www.dnastar.com/) was used to identify subgenome-specific single-nucleotide polymorphisms that enable reliable distinction of the A, B, and D subgenomes for a given triplet gene. Consequently, both pyrosequencing primers and gene-specific PCR amplification primers were designed successfully for a set of 12 triplet genes using the Soft Assay Design software (Supplemental Table S8). Biotin-labeled PCR products were immobilized on streptavidin-coated paramagnetic beads. Capture of biotinylated single-strand PCR products, annealing of the sequencing primer, and solid-phase pyrosequencing were performed following the manufacturer’s recommendations.
Data Processing and Statistical Analysis
The statistical significance of each comparison and graphical analyses were executed in R (version 3.1.0). The correlations between two biological replicates for a given sample were estimated using the Pearson correlation coefficient on log2(FPKM+1) in R. We detected the correlation coefficients ranging from 0.88 to 0.99 between two biological replicates of a given aneuploid or euploid strain (Supplemental Fig. S14A).
To estimate the statistical significance of dysregulated expression between each aneuploid strain versus the euploid CS, the χ2 test was applied with a 0.05 q value as cutoff. The aneuploid strains together with their common euploid CS were subjected to hierarchical clustering using a total of 12,565 genes that showed dysregulated expression in at least one aneuploid strain versus CS comparison. We performed hierarchical clustering by the pvclust package using the correlation distance for transformed expression values [log2(FPKM+1)] and average linkage in R against 1,000 bootstrap permutations. Results of the pvclust analysis provide the approximated unbiased and the bootstrap probability P values.
To determine whether the aneuploidy-induced trans-acting effects on gene expression were statistically more prevalent for a given subgenome, the proportion of dysregulated genes in each of the A, B, and D subgenomes was quantified. The Prop.test was applied separately for each aneuploid strain for this analysis. Similarly, the percentages of dysregulated genes by each normal chromosome in a given aneuploid strain versus the euploid wild-type were assessed based on the percentages of dysregulated genes out of the total number of expressed genes (excluding genes residing on the aneuploid chromosome) to determine whether the normal chromosomes in a given aneuploid strain were equally or differentially responsive to aneuploidy at the gene expression level. The Prop.test was applied with an adjusted P value by FDR.
To evaluate whether the dysregulated genes in response to aneuploidy would show an even distribution or be clustered to coexpressed aggregates along a given chromosome, we performed the lowess function in R to identify the potential existence of codysregulated expression domains by the method reported (Letourneau et al., 2014). Specifically, the smoothing of log2(fold change) between an aneuploid and the euploid wild type was conducted. The smoother span (bin width) was the averaged proportion of dysregulated genes locating on a given chromosome against the total number of dysregulated genes in each of the aneuploid versus euploid comparisons.
To analyze possible dosage compensation in the two studied aneuploid chromosomes (1A and 2A), we used the log2 ratio of aneuploid to euploid gene expression to plot the frequency distributions by a bin value of 0.1. The mean, median, and skewness of the distributions are shown. Pearson mode skewness was calculated by 3 × (mean − median)/sd. Genes exhibiting dosage effects and dosage compensation are shown by density plots.
To test whether homeologous chromosomes show coordinated changes in expression levels of the studied set of triplet genes in the three monosomic strains (M1A, M1B, and M1D), we calculated the Z statistic of averaged log2(fold change) of differentially expressed homeologs relative to the null hypothesis of Gaussian distribution with no expression reduction [mean = 0, σ2 equals the observed se of log2(fold change) of differentially expressed homeologs] and obtained the corresponding P value.
Phenotyping
A set of phenotypic traits was quantitatively measured in at least 30 individuals for each of the nine (except for Tri2A, some individuals of which were accidently damaged at the mature stage, thus impeding the measurement of some of the traits) aneuploid strains (Supplemental Table S1) along with their common euploid wild type (CS). The quantified traits included the fresh weight of 15-d-old seedlings and plant height, tiller number, spike length, spikelet number per spike, spikelet density, and seed setting all at the mature stage. Student’s t test was performed to test for statistical differences.
Accession Numbers
Data generated in this study are deposited in the National Center for Biotechnology Information Sequence Read Archive (accession no. SRP063352).
Supplemental Data
The following supplemental materials are available.
Supplemental Figure S1. Karyotypes of all aneuploid strains in the common hexaploid wheat CS based on FISH and GISH.
Supplemental Figure S2. Proportional Venn diagram showing the overlaps of dysregulated genes among three comparisons, N1A versus CS, N1ATri1B versus CS, and N1AT1B versus CS.
Supplemental Figure S3. Distribution of genes showing dysregulated expression along each normal chromosome due to the transcriptional response in each aneuploid strain (except for N1A, which is shown in Fig. 3B) of hexaploid wheat.
Supplemental Figure S4. Log2(fold change) of gene expression between each of the 10 aneuploid strains and euploid CS along each of the normal chromosomes of hexaploid wheat, depicted in gray.
Supplemental Figure S5. Frequency distribution of log2(fold change) in T1A (relative to the euploid CS).
Supplemental Figure S6. Dosage compensation for genes located on numerically altered chromosome 2A.
Supplemental Figure S7. Frequency distribution of genes on the aneuploid chromosome showing dosage effects and dosage compensation in the five aneuploid strains concerning 1A or 2A.
Supplemental Figure S8. Distinctly enriched GOs, in the molecular function category, by genes showing transcriptional responses to whole-chromosome aneuploidy in each of the 10 aneuploid strains of hexaploid wheat due to direct trans-effect or inverse trans-effect.
Supplemental Figure S9. Expression of homeologous members in a set of group 1 triplet genes in the two phenotypically compensated strains of hexaploid wheat.
Supplemental Figure S10. Hierarchical clustering analysis of expression similarity by homeologous members of a set of group 1 triplet genes in the three monosomics (M1A, M1B, and M1D) and their common euploid wild type (CS).
Supplemental Figure S11. Validation of the RNA-seq data by locus-specific cDNA pyrosequencing.
Supplemental Figure S12. Variation in three additional phenotypic traits in the whole-chromosome aneuploid strains relative to their isogenic euploid wild type (CS) of hexaploid wheat.
Supplemental Figure S13. Seedlings of the 10 aneuploid strains and their common euploid CS at 15 d after germination.
Supplemental Figure S14. Details of clean data generated in this study.
Supplemental Table S1. Detailed information of the 10 aneuploid strains and their common euploid CS of hexaploid wheat used in this study.
Supplemental Table S2. Statistical analysis among the four types of aneuploidy involving the same chromosome 1A.
Supplemental Table S3. Statistical analysis among the same type of aneuploidy of the three chromosomes belonging to homeologous group 1.
Supplemental Table S4. Statistical analysis between the aneuploid strains concerning chromosome 1A and 2A.
Supplemental Table S5. Statistical analysis between the two phenotypically compensated aneuploid strains.
Supplemental Table S6. Chromosome locations of regional domains in M1A and M1B.
Supplemental Table S7. Percentages of the dosage effect mediated by cis-effects in different aneuploid strains.
Supplemental Table S8. Detailed information for 12 triplet gene primers used in this study.
Supplemental Table S9. Average sequencing depth of each sample.
Acknowledgments
We thank Dr. Moshe Feldman of the Weizmann Institute of Science for providing original seeds of all the aneuploid strains and CS; Dr. Jonathan F. Wendel for constructive suggestions in the course of this study; and the four anonymous reviewers for their numerous valuable comments and constructive suggestions to enable significant improvement of the article.
Glossary
- CS
cv Chinese Spring
- GISH
genomic in situ hybridization
- FISH
fluorescence in situ hybridization
- FPKM
fragments per kilobase of gene per million mapped reads
- PDGs
percentage of dysregulated genes
- GEDD
gene expression dysregulation domain
- GO
Gene Ontology
- FDR
false discovery rate
Footnotes
This work was supported by the National Key Research and Development Program of China (2016YFD0102003), the National Natural Science Foundation of China (31290210), and the Program for Introducing Talents to Universities (B07017).
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