Metrics details Abstract Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi , illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species. Download PDF Main As one might expect from a genus with species living in deserts, in the tropics, on chains of volcanic islands and, often, commensally with humans, Drosophila species vary considerably in their morphology, ecology and behaviour 1.
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Genomics Abstract To characterize somatic alterations in colorectal carcinoma, we conducted a genome-scale analysis of samples, analysing exome sequence, DNA copy number, promoter methylation and messenger RNA and microRNA expression.
A subset of these samples 97 underwent low-depth-of-coverage whole-genome sequencing. Excluding the hypermutated cancers, colon and rectum cancers were found to have considerably similar patterns of genomic alteration. Recurrent copy-number alterations include potentially drug-targetable amplifications of ERBB2 and newly discovered amplification of IGF2. Integrative analyses suggest new markers for aggressive colorectal carcinoma and an important role for MYC-directed transcriptional activation and repression.
Download PDF Main The Cancer Genome Atlas project plans to profile genomic changes in 20 different cancer types and has so far published results on two cancer types 1 , 2. We now present results from multidimensional analyses of human colorectal carcinoma CRC. CRC is an important contributor to cancer mortality and morbidity. The distinction between the colon and the rectum is largely anatomical, but it has both surgical and radiotherapeutic management implications and it may have an impact on prognosis.
Most investigators divide CRC biologically into those with microsatellite instability MSI; located primarily in the right colon and frequently associated with the CpG island methylator phenotype CIMP and hyper-mutation and those that are microsatellite stable but chromosomally unstable.
A rich history of investigations for a review see ref. Large-scale sequencing analyses 4 , 5 , 6 have identified numerous recurrently mutated genes and a recurrent chromosomal translocation.
Despite this background, we have not had a fully integrated view of the genetic and genomic changes and their significance for colorectal tumorigenesis. Further insight into these changes may enable deeper understanding of the pathophysiology of CRC and may identify potential therapeutic targets. Results Tumour and normal pairs were analysed by different platforms.
The specific numbers of samples analysed by each platform are shown in Supplementary Table 1. Exome-sequence analysis To define the mutational spectrum, we performed exome capture DNA sequencing on tumour and normal pairs all mutations are listed in Supplementary Table 2.
The somatic mutation rates varied considerably among the samples. Figure 1: Mutation frequencies in human CRC. Note a clear separation of hypermutated and non-hypermutated samples. Inset, mutations in mismatch-repair genes and POLE among the hypermutated samples. The order of the samples is the same as in the main graph. Blue bars represent genes identified by the MutSig algorithm and black bars represent genes identified by manual examination of sequence data.
Gene mutations Overall, we identified 32 somatic recurrently mutated genes defined by MutSig 11 and manual curation in the hypermutated and non-hypermutated cancers Fig.
After removal of non-expressed genes, there were 15 and 17 in the hypermutated and non-hypermutated cancers, respectively Fig. As expected, the mutated KRAS and NRAS genes usually had oncogenic codon 12 and 13 or codon 61 mutations, whereas the remaining genes had inactivating mutations. Mutations in SOX9, a gene important for cell differentiation in the intestinal stem cell niche 13 , 14 , have not been associated previously with human cancer, but all nine mutated alleles in the non-hypermutated CRCs were frameshift or nonsense mutations.
Other genes, including TGFBR2, were mutated recurrently in the hypermutated cancers, but not in the non-hypermutated samples. These findings indicate that hypermutated and non-hypermutated tumours progress through different sequences of genetic events. When we specifically examined 28 genes with long mononucleotide repeats in their coding sequences, we found that the rate of frameshift mutation was 3.
Mutation rate and methylation patterns As mentioned above, patients with colon and rectal tumours are managed differently 17 , and epidemiology also highlights differences between the two An initial integrative analysis of MSI status, somatic copy-number alterations SCNAs , CIMP status and gene-expression profiles of colonic and 62 rectal tumours enabled us to examine possible biological differences between tumours in the two locations.
On the basis of this result, we merged the two for all subsequent analyses. Figure 2: Integrative analysis of genomic changes in CRCs.
Non-hypermutated tumours originating from different sites are virtually indistinguishable from each other on the basis of their copy-number alteration patterns, DNA methylation or gene-expression patterns.
Copy-number changes of the 22 autosomes are shown in shades of red for copy-number gains and shades of blue for copy-number losses. Full size image Unsupervised clustering of the promoter DNA methylation profiles of colorectal tumours identified four subgroups Supplementary Fig.
The two non-CIMP clusters were predominantly from tumours that were non-hypermutated and derived from different anatomic locations. Of these tumours, 97 were also analysed by low-depth-of-coverage low-pass whole-genome sequencing. No difference was found between microsatellite-stable and -unstable hypermutated tumours Supplementary Fig. There were several previously well-defined arm-level changes, including gains of 1q, 7p and q, 8p and q, 12q, 13q, 19q, and 20p and q ref.
Supplementary Fig. Other significantly deleted chromosome arms were 1p, 4q, 5q, 8p, 14q, 15q, 20p and 22q. We identified 28 recurrent deletion peaks Supplementary Fig. A significant focal deletion of 10p There were 17 regions of significant focal amplification Supplementary Table 4.
Some of these were superimposed on broad gains of chromosome arms, and included a peak at 13q An amplicon at 17q ERBB2 amplifications have been described in colon, breast and gastro—oesophageal tumours, and breast and gastric cancers bearing these amplifications have been treated effectively with the anti-ERBB2 antibody trastuzumab 20 , 21 , Immediately adjacent to the amplified region is ASCL2, a transcription factor active in specifying intestinal stem-cell fate Although ASCL2 has been implicated as a target of amplification in CRC 23 , 24 , 25 , it was consistently outside the region of amplification and its expression was not correlated with copy-number changes.
These observations suggest that IGF2 and miR are candidate functional targets of 11p MiR may also have a role in CRC pathogenesis Figure 3: Copy-number changes and structural aberrations in CRC. Each row represents a patient; amplified regions are shown in red. The structure of the two genes, locations of the breakpoints leading to the translocation and circular representations of all rearrangements in tumours with a fusion are shown.
The inner ring represents copy-number changes blue denotes loss, pink denotes gain. Translocations To identify new chromosomal translocations, we performed low-pass, paired-end, whole-genome sequencing on 97 tumours with matched normal samples.
Despite the low genome coverage, we detected candidate interchromosomal translocation events range, 0—10 per tumour.
Among these events, had one or both breakpoints in an intergenic region, whereas the remaining 38 juxtaposed coding regions of two genes in putative fusion events, of which 18 were predicted to code for in-frame events Supplementary Table 6. We also observed 21 cases of translocation involving TTC28 located on chromosome 22 Supplementary Table 6. In all cases the fusions predict inactivation of TTC28, which has been identified as a target of P53 and an inhibitor of tumour cell growth Altered pathways in CRC Integrated analysis of mutations, copy number and mRNA expression changes in tumours with complete data enriched our understanding of how some well-defined pathways are deregulated.
Figure 4: Diversity and frequency of genetic changes leading to deregulation of signalling pathways in CRC. Alterations are defined by somatic mutations, homozygous deletions, high-level focal amplifications, and, in some cases, by significant up- or downregulation of gene expression IGF2, FZD10, SMAD4. Alteration frequencies are expressed as a percentage of all cases. Red denotes activated genes and blue denotes inactivated genes. Bottom panel shows for each sample if at least one gene in each of the five pathways described in this figure is altered.
SOX9 has been suggested to have a role in cancer, but no mutations have previously been described. Interestingly, many of these alterations were found in tumours that harbour APC mutations, suggesting that multiple lesions affecting the WNT signalling pathway confer selective advantage.
We also evaluated mutations in the erythroblastic leukemia viral oncogene homolog ERBB family of receptors because of the translational relevance of such mutations. These results indicate that simultaneous inhibition of the RAS and PI3K pathways may be required to achieve therapeutic benefit.
The analysis showed a number of new characteristics of CRC Fig. These findings are consistent with patterns deduced from genetic alterations Fig. The analysis also identified several gene networks altered across all tumour samples and those with differential alterations in hypermutated versus non-hypermutated samples Supplementary Table 7 , Supplementary Data on the Cancer Genome Atlas publication webpage.
Figure 5: Integrative analyses of multiple data sets. Blue denotes under-expressed relative to normal and red denotes overexpressed relative to normal. Some of the pathways deduced by this method are shown on the right.
NHEJ, non-homologous end joining. Molecular signatures rows that show a statistically significant association with tumour aggressiveness according to selected clinical assays columns are shown in colour, with red indicating markers of tumour aggressiveness and blue indicating the markers of less-aggressive tumours. Colour intensity and score is in accordance with the strength of an individual clinical—molecular association, and is proportional to log10 P , where P is the P value for that association.
Full size image Because most of the tumours used in this study were derived from a prospective collection, survival data are not available. However, the tumours can be classified as aggressive or non-aggressive on the basis of tumour stage, lymph node status, distant metastasis and vascular invasion at the time of surgery.
We found numerous molecular signatures associated with tumour aggressiveness, a subset of which is shown in Fig. They include specific focal amplifications and deletions, and altered gene-expression levels, including those of SCN5A ref.
Interestingly, a number of genomic regions have multiple molecular associations with tumour aggressiveness that manifest as clinically related genomic hotspots. Examples of this are the region 20q Discussion This comprehensive integrative analysis of colorectal tumour and normal pairs provides a number of insights into the biology of CRC and identifies potential therapeutic targets.
To identify possible biological differences in colon and rectum tumours, we found, in the non-hypermutated tumours irrespective of their anatomical origin, the same type of copy number, expression profile, DNA methylation and miRNA changes.
However, there were some differences between tumours from the right colon and all other sites. Hypermethylation was more common in the right colon, and three-quarters of hypermutated samples came from the same site, although not all of them had MSI Fig. Why most of the hypermutated samples came from the right colon and why there are two classes of tumours at this site is not known. The origins of the colon from embryonic midgut and hindgut may provide an explanation.
As the survival rate of patients with high MSI-related cancers is better and these cancers are hypermutated, mutation rate may be a better prognostic indicator. Whole-exome sequencing and integrative analysis of genomic data provided further insights into the pathways that are dysregulated in CRC. To our knowledge, SOX9 has not previously been described as frequently mutated in any human cancer.
We also compared our results with other large-scale analyses 6 and found many similarities and few differences in mutated genes Supplementary Table 3.
Our data suggest a number of therapeutic approaches to CRC. Our analyses show that non-hypermutated adenocarcinomas of the colon and rectum are not distinguishable at the genomic level.
Mastering the Geometry of Market Energy
Background and early life Robert Drummond was born on 13 November , the 3rd surviving son of at least 13 children of William Drummond, 4th Viscount Strathallan and his wife Margaret, daughter of Lord William Murray. William Drummond was a prominent Jacobite. He had taken part in the Rising, and had been taken prisoner at Sherrifmuir. Robert Drummond was brought up on the family estate at Machany in Perthshire, but in he and his younger brother Henry were sent to London to live with their uncle Andrew Drummond. John suffered from ill health, leaving Robert to take most responsibility for the business. It soon became evident that the bank needed an additional partner, and in Robert asked his brother Henry, who had left the bank to pursue other business interests, to join the partnership.
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Charles Drummond (1790-1858)
Charles Drummond (1759-1823)