KEL1 | GeneID:856563 | Saccharomyces cerevisiae

AAB68991   NP_012028   P38853   S46769  

1. [ ] Tarassov K, et al. (2008) "An in vivo map of the yeast protein interactome." Science. 320(5882):1465-1470. PMID:18467557

Protein interactions regulate the systems-level behavior of cells; thus, deciphering the structure and dynamics of protein interaction networks in their cellular context is a central goal in biology. We have performed a genome-wide in vivo screen for protein-protein interactions in Saccharomyces cerevisiae by means of a protein-fragment complementation assay (PCA). We identified 2770 interactions among 1124 endogenously expressed proteins. Comparison with previous studies confirmed known interactions, but most were not known, revealing a previously unexplored subspace of the yeast protein interactome. The PCA detected structural and topological relationships between proteins, providing an 8-nanometer-resolution map of dynamically interacting complexes in vivo and extended networks that provide insights into fundamental cellular processes, including cell polarization and autophagy, pathways that are evolutionarily conserved and central to both development and human health.

2. [ ] Collins SR, et al. (2007) "Toward a comprehensive atlas of the physical interactome of Saccharomyces cerevisiae." Mol Cell Proteomics. 6(3):439-450. PMID:17200106

Defining protein complexes is critical to virtually all aspects of cell biology. Two recent affinity purification/mass spectrometry studies in Saccharomyces cerevisiae have vastly increased the available protein interaction data. The practical utility of such high throughput interaction sets, however, is substantially decreased by the presence of false positives. Here we created a novel probabilistic metric that takes advantage of the high density of these data, including both the presence and absence of individual associations, to provide a measure of the relative confidence of each potential protein-protein interaction. This analysis largely overcomes the noise inherent in high throughput immunoprecipitation experiments. For example, of the 12,122 binary interactions in the general repository of interaction data (BioGRID) derived from these two studies, we marked 7504 as being of substantially lower confidence. Additionally, applying our metric and a stringent cutoff we identified a set of 9074 interactions (including 4456 that were not among the 12,122 interactions) with accuracy comparable to that of conventional small scale methodologies. Finally we organized proteins into coherent multisubunit complexes using hierarchical clustering. This work thus provides a highly accurate physical interaction map of yeast in a format that is readily accessible to the biological community.

3. [ ] McClellan AJ, et al. (2007) "Diverse cellular functions of the Hsp90 molecular chaperone uncovered using systems approaches." Cell. 131(1):121-135. PMID:17923092

A comprehensive understanding of the cellular functions of the Hsp90 molecular chaperone has remained elusive. Although Hsp90 is essential, highly abundant under normal conditions, and further induced by environmental stress, only a limited number of Hsp90 "clients" have been identified. To define Hsp90 function, a panel of genome-wide chemical-genetic screens in Saccharomyces cerevisiae were combined with bioinformatic analyses. This approach identified several unanticipated functions of Hsp90 under normal conditions and in response to stress. Under normal growth conditions, Hsp90 plays a major role in various aspects of the secretory pathway and cellular transport; during environmental stress, Hsp90 is required for the cell cycle, meiosis, and cytokinesis. Importantly, biochemical and cell biological analyses validated several of these Hsp90-dependent functions, highlighting the potential of our integrated global approach to uncover chaperone functions in the cell.

4. [ ] Gavin AC, et al. (2006) "Proteome survey reveals modularity of the yeast cell machinery." Nature. 440(7084):631-636. PMID:16429126

Protein complexes are key molecular entities that integrate multiple gene products to perform cellular functions. Here we report the first genome-wide screen for complexes in an organism, budding yeast, using affinity purification and mass spectrometry. Through systematic tagging of open reading frames (ORFs), the majority of complexes were purified several times, suggesting screen saturation. The richness of the data set enabled a de novo characterization of the composition and organization of the cellular machinery. The ensemble of cellular proteins partitions into 491 complexes, of which 257 are novel, that differentially combine with additional attachment proteins or protein modules to enable a diversification of potential functions. Support for this modular organization of the proteome comes from integration with available data on expression, localization, function, evolutionary conservation, protein structure and binary interactions. This study provides the largest collection of physically determined eukaryotic cellular machines so far and a platform for biological data integration and modelling.

5. [ ] Krogan NJ, et al. (2006) "Global landscape of protein complexes in the yeast Saccharomyces cerevisiae." Nature. 440(7084):637-643. PMID:16554755

Identification of protein-protein interactions often provides insight into protein function, and many cellular processes are performed by stable protein complexes. We used tandem affinity purification to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae. Each preparation was analysed by both matrix-assisted laser desorption/ionization-time of flight mass spectrometry and liquid chromatography tandem mass spectrometry to increase coverage and accuracy. Machine learning was used to integrate the mass spectrometry scores and assign probabilities to the protein-protein interactions. Among 4,087 different proteins identified with high confidence by mass spectrometry from 2,357 successful purifications, our core data set (median precision of 0.69) comprises 7,123 protein-protein interactions involving 2,708 proteins. A Markov clustering algorithm organized these interactions into 547 protein complexes averaging 4.9 subunits per complex, about half of them absent from the MIPS database, as well as 429 additional interactions between pairs of complexes. The data (all of which are available online) will help future studies on individual proteins as well as functional genomics and systems biology.

6. [ ] Knaus M, et al. (2005) "The Bud14p-Glc7p complex functions as a cortical regulator of dynein in budding yeast." EMBO J. 24(17):3000-3011. PMID:16107882

Regulated interactions between microtubules (MTs) and the cell cortex control MT dynamics and position the mitotic spindle. In eukaryotic cells, the adenomatous polyposis coli/Kar9p and dynein/dynactin pathways are involved in guiding MT plus ends and MT sliding along the cortex, respectively. Here we identify Bud14p as a novel cortical activator of the dynein/dynactin complex in budding yeast. Bud14p accumulates at sites of polarized growth and the mother-bud neck during cytokinesis. The localization to bud and shmoo tips requires an intact actin cytoskeleton and the kelch-domain-containing proteins Kel1p and Kel2p. While cells lacking Bud14p function fail to stabilize the pre-anaphase spindle at the mother-bud neck, overexpression of Bud14p is toxic and leads to elongated astral MTs and increased dynein-dependent sliding along the cell cortex. Bud14p physically interacts with the type-I phosphatase Glc7p, and localizes Glc7p to the bud cortex. Importantly, the formation of Bud14p-Glc7p complexes is necessary to regulate MT dynamics at the cortex. Taken together, our results suggest that Bud14p functions as a regulatory subunit of the Glc7p type-I phosphatase to stabilize MT interactions specifically at sites of polarized growth.

7. [ ] Ptacek J, et al. (2005) "Global analysis of protein phosphorylation in yeast." Nature. 438(7068):679-684. PMID:16319894

Protein phosphorylation is estimated to affect 30% of the proteome and is a major regulatory mechanism that controls many basic cellular processes. Until recently, our biochemical understanding of protein phosphorylation on a global scale has been extremely limited; only one half of the yeast kinases have known in vivo substrates and the phosphorylating kinase is known for less than 160 phosphoproteins. Here we describe, with the use of proteome chip technology, the in vitro substrates recognized by most yeast protein kinases: we identified over 4,000 phosphorylation events involving 1,325 different proteins. These substrates represent a broad spectrum of different biochemical functions and cellular roles. Distinct sets of substrates were recognized by each protein kinase, including closely related kinases of the protein kinase A family and four cyclin-dependent kinases that vary only in their cyclin subunits. Although many substrates reside in the same cellular compartment or belong to the same functional category as their phosphorylating kinase, many others do not, indicating possible new roles for several kinases. Furthermore, integration of the phosphorylation results with protein-protein interaction and transcription factor binding data revealed novel regulatory modules. Our phosphorylation results have been assembled into a first-generation phosphorylation map for yeast. Because many yeast proteins and pathways are conserved, these results will provide insights into the mechanisms and roles of protein phosphorylation in many eukaryotes.

8. [ ] Archambault V, et al. (2004) "Targeted proteomic study of the cyclin-Cdk module." Mol Cell. 14(6):699-711. PMID:15200949

The cell division cycle of the yeast S. cerevisiae is driven by one Cdk (cyclin-dependent kinase), which becomes active when bound to one of nine cyclin subunits. Elucidation of Cdk substrates and other Cdk-associated proteins is essential for a full understanding of the cell cycle. Here, we report the results of a targeted proteomics study using affinity purification coupled to mass spectrometry. Our study identified numerous proteins in association with particular cyclin-Cdk complexes. These included phosphorylation substrates, ubiquitination-degradation proteins, adaptors, and inhibitors. Some associations were previously known, and for others, we confirmed their specificity and biological relevance. Using a hypothesis-driven mass spectrometric approach, we also mapped in vivo phosphorylation at Cdk consensus motif-containing peptides within several cyclin-associated candidate Cdk substrates. Our results demonstrate that this approach can be used to detect a host of transient and dynamic protein associations within a biological module.

9. [ ] Ubersax JA, et al. (2003) "Targets of the cyclin-dependent kinase Cdk1." Nature. 425(6960):859-864. PMID:14574415

The events of cell reproduction are governed by oscillations in the activities of cyclin-dependent kinases (Cdks). Cdks control the cell cycle by catalysing the transfer of phosphate from ATP to specific protein substrates. Despite their importance in cell-cycle control, few Cdk substrates have been identified. Here, we screened a budding yeast proteomic library for proteins that are directly phosphorylated by Cdk1 in whole-cell extracts. We identified about 200 Cdk1 substrates, several of which are phosphorylated in vivo in a Cdk1-dependent manner. The identities of these substrates reveal that Cdk1 employs a global regulatory strategy involving phosphorylation of other regulatory molecules as well as phosphorylation of the molecular machines that drive cell-cycle events. Detailed analysis of these substrates is likely to yield important insights into cell-cycle regulation.

10. [ ] Gavin AC, et al. (2002) "Functional organization of the yeast proteome by systematic analysis of protein complexes." Nature. 415(6868):141-147. PMID:11805826

Most cellular processes are carried out by multiprotein complexes. The identification and analysis of their components provides insight into how the ensemble of expressed proteins (proteome) is organized into functional units. We used tandem-affinity purification (TAP) and mass spectrometry in a large-scale approach to characterize multiprotein complexes in Saccharomyces cerevisiae. We processed 1,739 genes, including 1,143 human orthologues of relevance to human biology, and purified 589 protein assemblies. Bioinformatic analysis of these assemblies defined 232 distinct multiprotein complexes and proposed new cellular roles for 344 proteins, including 231 proteins with no previous functional annotation. Comparison of yeast and human complexes showed that conservation across species extends from single proteins to their molecular environment. Our analysis provides an outline of the eukaryotic proteome as a network of protein complexes at a level of organization beyond binary interactions. This higher-order map contains fundamental biological information and offers the context for a more reasoned and informed approach to drug discovery.

11. [ ] Ho Y, et al. (2002) "Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry." Nature. 415(6868):180-183. PMID:11805837

The recent abundance of genome sequence data has brought an urgent need for systematic proteomics to decipher the encoded protein networks that dictate cellular function. To date, generation of large-scale protein-protein interaction maps has relied on the yeast two-hybrid system, which detects binary interactions through activation of reporter gene expression. With the advent of ultrasensitive mass spectrometric protein identification methods, it is feasible to identify directly protein complexes on a proteome-wide scale. Here we report, using the budding yeast Saccharomyces cerevisiae as a test case, an example of this approach, which we term high-throughput mass spectrometric protein complex identification (HMS-PCI). Beginning with 10% of predicted yeast proteins as baits, we detected 3,617 associated proteins covering 25% of the yeast proteome. Numerous protein complexes were identified, including many new interactions in various signalling pathways and in the DNA damage response. Comparison of the HMS-PCI data set with interactions reported in the literature revealed an average threefold higher success rate in detection of known complexes compared with large-scale two-hybrid studies. Given the high degree of connectivity observed in this study, even partial HMS-PCI coverage of complex proteomes, including that of humans, should allow comprehensive identification of cellular networks.

12. [ ] Kumar A, et al. (2002) "Subcellular localization of the yeast proteome." Genes Dev. 16(6):707-719. PMID:11914276

Protein localization data are a valuable information resource helpful in elucidating eukaryotic protein function. Here, we report the first proteome-scale analysis of protein localization within any eukaryote. Using directed topoisomerase I-mediated cloning strategies and genome-wide transposon mutagenesis, we have epitope-tagged 60% of the Saccharomyces cerevisiae proteome. By high-throughput immunolocalization of tagged gene products, we have determined the subcellular localization of 2744 yeast proteins. Extrapolating these data through a computational algorithm employing Bayesian formalism, we define the yeast localizome (the subcellular distribution of all 6100 yeast proteins). We estimate the yeast proteome to encompass approximately 5100 soluble proteins and >1000 transmembrane proteins. Our results indicate that 47% of yeast proteins are cytoplasmic, 13% mitochondrial, 13% exocytic (including proteins of the endoplasmic reticulum and secretory vesicles), and 27% nuclear/nucleolar. A subset of nuclear proteins was further analyzed by immunolocalization using surface-spread preparations of meiotic chromosomes. Of these proteins, 38% were found associated with chromosomal DNA. As determined from phenotypic analyses of nuclear proteins, 34% are essential for spore viability--a percentage nearly twice as great as that observed for the proteome as a whole. In total, this study presents experimentally derived localization data for 955 proteins of previously unknown function: nearly half of all functionally uncharacterized proteins in yeast. To facilitate access to these data, we provide a searchable database featuring 2900 fluorescent micrographs at http://ygac.med.yale.edu.

13. [ ] Burchett SA, et al. (2002) "Regulation of stress response signaling by the N-terminal dishevelled/EGL-10/pleckstrin domain of Sst2, a regulator of G protein signaling in Saccharomyces cerevisiae." J Biol Chem. 277(25):22156-22167. PMID:11940600

All members of the regulator of G protein signaling (RGS) family contain a conserved core domain that can accelerate G protein GTPase activity. The RGS in yeast, Sst2, can inhibit a G protein signal leading to mating. In addition, some RGS proteins contain an N-terminal domain of unknown function. Here we use complementary whole genome analysis methods to investigate the function of the N-terminal Sst2 domain. To identify a signaling pathway regulated by N-Sst2, we performed genome-wide transcription profiling of cells expressing this fragment alone and found differences in 53 transcripts. Of these, 40 are induced by N-Sst2, and nearly all contain a stress response element (STRE) in the promoter region. To identify components of a signaling pathway leading from N-Sst2 to STREs, we performed a genome-wide two-hybrid analysis using N-Sst2 as bait and found 17 interacting proteins. To identify the functionally relevant interacting proteins, we analyzed all of the available gene deletion mutants and found three (vps36 Delta, pep12 Delta, and tlg2 Delta) that induce STRE and also repress pheromone-dependent transcription. We selected VPS36 for further characterization. A vps36 Delta mutation diminishes signaling by pheromone as well as by downstream components including the G protein, effector kinase (Ste11), and transcription factor (Ste12). Conversely, overexpression of Vps36 enhances the pheromone response in sst2 Delta cells but not in wild type. These findings indicate that Vps36 and Sst2 have opposite and opposing effects on the pheromone and stress response pathways, with Vps36 acting downstream of the G protein and independently of Sst2 RGS activity.

14. [ ] Hofken T, et al. (2002) "A role for cell polarity proteins in mitotic exit." EMBO J. 21(18):4851-4862. PMID:12234925

The budding yeast mitotic exit network (MEN) is a signal transduction cascade that controls exit from mitosis by facilitating the release of the cell cycle phosphatase Cdc14 from the nucleolus. The G protein Tem1 regulates MEN activity. The Tem1 guanine nucleotide exchange factor (GEF) Lte1 associates with the cortex of the bud and activates the MEN upon the formation of an anaphase spindle. Thus, the cell cortex has an important but ill-defined role in MEN regulation. Here, we describe a network of conserved cortical cell polarity proteins that have key roles in mitotic exit. The Rho-like GTPase Cdc42, its GEF Cdc24 and its effector Cla4 [a member of the p21-activated kinases (PAKs)] control the initial binding and activation of Lte1 to the bud cortex. Moreover, Cdc24, Cdc42 and Ste20, another PAK, probably function parallel to Lte1 in facilitating mitotic exit. Finally, the cell polarity proteins Kel1 and Kel2 are present in complexes with both Lte1 and Tem1, and negatively regulate mitotic exit.

15. [ ] Seshan A, et al. (2002) "Control of Lte1 localization by cell polarity determinants and Cdc14." Curr Biol. 12(24):2098-2110. PMID:12498684

BACKGROUND: The putative guanine nucleotide exchange factor Lte1 plays an essential role in promoting exit from mitosis at low temperatures. Lte1 is thought to activate a Ras-like signaling cascade, the mitotic exit network (MEN). MEN promotes the release of the protein phosphatase Cdc14 from the nucleolus during anaphase, and this release is a prerequisite for exit from mitosis. Lte1 is present throughout the cell during G1 but is sequestered in the bud during S phase and mitosis by an unknown mechanism. RESULTS: We show that anchorage of Lte1 in the bud requires septins, the cell polarity determinants Cdc42 and Cla4, and Kel1. Lte1 physically associates with Kel1 and requires Kel1 for its localization in the bud, suggesting a role for Kel1 in anchoring Lte1 at the bud cortex. Our data further implicate the PAK-like protein kinase Cla4 in controlling Lte1 phosphorylation and localization. CLA4 is required for Lte1 phosphorylation and bud localization. Furthermore, when overexpressed, CLA4 induces Lte1 phosphorylation and localization to regions of polarized growth. Finally, we show that Cdc14, directly or indirectly, controls Lte1 dephosphorylation and delocalization from the bud during exit from mitosis. CONCLUSION: Restriction of Lte1 to the bud cortex depends on the cortical proteins Cdc42 and Kel1 and the septin ring. Cla4 and Cdc14 promote and demote Lte1 localization at and from the bud cortex, respectively, suggesting not only that the phosphorylation status of Lte1 controls its localization but also indicating that Cla4 and Cdc14 are key regulators of the spatial asymmetry of Lte1.

16. [ ] Uetz P, et al. (2000) "A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae." Nature. 403(6770):623-627. PMID:10688190

Two large-scale yeast two-hybrid screens were undertaken to identify protein-protein interactions between full-length open reading frames predicted from the Saccharomyces cerevisiae genome sequence. In one approach, we constructed a protein array of about 6,000 yeast transformants, with each transformant expressing one of the open reading frames as a fusion to an activation domain. This array was screened by a simple and automated procedure for 192 yeast proteins, with positive responses identified by their positions in the array. In a second approach, we pooled cells expressing one of about 6,000 activation domain fusions to generate a library. We used a high-throughput screening procedure to screen nearly all of the 6,000 predicted yeast proteins, expressed as Gal4 DNA-binding domain fusion proteins, against the library, and characterized positives by sequence analysis. These approaches resulted in the detection of 957 putative interactions involving 1,004 S. cerevisiae proteins. These data reveal interactions that place functionally unclassified proteins in a biological context, interactions between proteins involved in the same biological function, and interactions that link biological functions together into larger cellular processes. The results of these screens are shown here.

17. [ ] Pardo M, et al. (2000) "A proteomic approach for the study of Saccharomyces cerevisiae cell wall biogenesis." Electrophoresis. 21(16):3396-3410. PMID:11079560

In fungi, cell shape is determined by the presence of a rigid cell wall which separates the cell from the extracellular medium. This highly dynamic structure is essential for the maintenance of cell integrity and is involved in several phenomena such as flocculation, adherence and pathogenicity. The composition of the fungal cell wall is well known, but issues such as the assembly and remodeling of its components remain poorly understood. In an attempt to study the de novo construction of the yeast cell wall, we have undertaken a large-scale proteomic approach to analyze the proteins secreted by regenerating protoplasts. Upon incubation of protoplasts in regenerating conditions, numerous proteins are secreted into the culture medium. These presumably include proteins destined for the cell wall, comprising both structural proteins as well as enzymes involved in cell wall biogenesis. This work reports the establishment of a reference map of proteins secreted by regenerating protoplasts by means of two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) and their identification by mass spectrometry. Thirty-two different proteins have been identified, including known cell wall proteins, glycolytic enzymes, heat shock proteins, and proteins involved in several other processes. Using this approach, novel proteins possibly involved in cell wall construction have also been identified. This reference map will allow comparative analyses to be carried out on a selected collection of mutants affected in the cell wall.

18. [ ] Newman JR, et al. (2000) "A computationally directed screen identifying interacting coiled coils from Saccharomyces cerevisiae." Proc Natl Acad Sci U S A. 97(24):13203-13208. PMID:11087867

Computational methods can frequently identify protein-interaction motifs in otherwise uncharacterized open reading frames. However, the identification of candidate ligands for these motifs (e.g., so that partnering can be determined experimentally in a directed manner) is often beyond the scope of current computational capabilities. One exception is provided by the coiled-coil interaction motif, which consists of two or more alpha helices that wrap around each other: the ligands for coiled-coil sequences are generally other coiled-coil sequences, thereby greatly simplifying the motif/ligand recognition problem. Here, we describe a two-step approach to identifying protein-protein interactions mediated by two-stranded coiled coils that occur in Saccharomyces cerevisiae. Coiled coils from the yeast genome are first predicted computationally, by using the multicoil program, and associations between coiled coils are then determined experimentally by using the yeast two-hybrid assay. We report 213 unique interactions between 162 putative coiled-coil sequences. We evaluate the resulting interactions, focusing on associations identified between components of the spindle pole body (the yeast centrosome).

19. [ ] Philips J, et al. (1998) "Identification of Kel1p, a kelch domain-containing protein involved in cell fusion and morphology in Saccharomyces cerevisiae." J Cell Biol. 143(2):375-389. PMID:9786949

We showed previously that protein kinase C, which is required to maintain cell integrity, negatively regulates cell fusion (Philips, J., and I. Herskowitz. 1997. J. Cell Biol. 138:961-974). To identify additional genes involved in cell fusion, we looked for genes whose overexpression relieved the defect caused by activated alleles of Pkc1p. This strategy led to the identification of a novel gene, KEL1, which encodes a protein composed of two domains, one containing six kelch repeats, a motif initially described in the Drosophila protein Kelch (Xue, F., and L. Cooley. 1993. Cell. 72:681- 693), and another domain predicted to form coiled coils. Overexpression of KEL1 also suppressed the defect in cell fusion of spa2Delta and fps1Delta mutants. KEL2, which corresponds to ORF YGR238c, encodes a protein highly similar to Kel1p. Its overexpression also suppressed the mating defect associated with activated Pkc1p. Mutants lacking KEL1 exhibited a moderate defect in cell fusion that was exacerbated by activated alleles of Pkc1p or loss of FUS1, FUS2, or FPS1, but not by loss of SPA2. kel1Delta mutants form cells that are elongated and heterogeneous in shape, indicating that Kel1p is also required for proper morphology during vegetative growth. In contrast, kel2Delta mutants were not impaired in cell fusion or morphology. Both Kel1p and Kel2p localized to the site where cell fusion occurs during mating and to regions of polarized growth during vegetative growth. Coimmunoprecipitation and two-hybrid analyses indicated that Kel1p and Kel2p physically interact. We conclude that Kel1p has a role in cell morphogenesis and cell fusion and may antagonize the Pkc1p pathway.

20. [ ] Goffeau A, et al. (1996) "Life with 6000 genes." Science. 274(5287):546, 563-546, 567. PMID:8849441

The genome of the yeast Saccharomyces cerevisiae has been completely sequenced through a worldwide collaboration. The sequence of 12,068 kilobases defines 5885 potential protein-encoding genes, approximately 140 genes specifying ribosomal RNA, 40 genes for small nuclear RNA molecules, and 275 transfer RNA genes. In addition, the complete sequence provides information about the higher order organization of yeast's 16 chromosomes and allows some insight into their evolutionary history. The genome shows a considerable amount of apparent genetic redundancy, and one of the major problems to be tackled during the next stage of the yeast genome project is to elucidate the biological functions of all of these genes.

21. [ ] Johnston M, et al. (1994) "Complete nucleotide sequence of Saccharomyces cerevisiae chromosome VIII." Science. 265(5181):2077-2082. PMID:8091229

The complete nucleotide sequence of Saccharomyces cerevisiae chromosome VIII reveals that it contains 269 predicted or known genes (300 base pairs or larger). Fifty-nine of these genes (22 percent) were previously identified. Of the 210 novel genes, 65 are predicted to encode proteins that are similar to other proteins of known or predicted function. Sixteen genes appear to be relatively recently duplicated. On average, there is one gene approximately every 2 kilobases. Although the coding density and base composition across the chromosome are not uniform, no regular pattern of variation is apparent.