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We have sequenced five distinct mitochondrial genomes in maize: two fertile cytotypes (NA and the previously reported NB) and three cytoplasmic-male-sterile cytotypes (CMS-C, CMS-S, and CMS-T). Their genome sizes range from 535,825 bp in CMS-T to 739,719 bp in CMS-C. Large duplications (0.5–120 kb) account for most of the size increases. Plastid DNA accounts for 2.3–4.6% of each mitochondrial genome. The genomes share a minimum set of 51 genes for 33 conserved proteins, three ribosomal RNAs, and 15 transfer RNAs. Numbers of duplicate genes and plastid-derived tRNAs vary among cytotypes. A high level of sequence conservation exists both within and outside of genes (1.65–7.04 substitutions/10 kb in pairwise comparisons). However, sequence losses and gains are common: integrated plastid and plasmid sequences, as well as noncoding “native” mitochondrial sequences, can be lost with no phenotypic consequence. The organization of the different maize mitochondrial genomes varies dramatically; even between the two fertile cytotypes, there are 16 rearrangements. Comparing the finished shotgun sequences of multiple mitochondrial genomes from the same species suggests which genes and open reading frames are potentially functional, including which chimeric ORFs are candidate genes for cytoplasmic male sterility. This method identified the known CMS-associated ORFs in CMS-S and CMS-T, but not in CMS-C.

Salmonella enterica serovars often have a broad host range, and some cause both gastrointestinal and systemic disease. But the serovars Paratyphi A and Typhi are restricted to humans and cause only systemic disease. It has been estimated that Typhi arose in the last few thousand years. The sequence and microarray analysis of the Paratyphi A genome indicates that it is similar to the Typhi genome but suggests that it has a more recent evolutionary origin. Both genomes have independently accumulated many pseudogenes among their ∼4,400 protein coding sequences: 173 in Paratyphi A and ∼210 in Typhi. The recent convergence of these two similar genomes on a similar phenotype is subtly reflected in their genotypes: only 30 genes are degraded in both serovars. Nevertheless, these 30 genes include three known to be important in gastroenteritis, which does not occur in these serovars, and four for Salmonella -translocated effectors, which are normally secreted into host cells to subvert host functions. Loss of function also occurs by mutation in different genes in the same pathway ( e.g. , in chemotaxis and in the production of fimbriae).

In this study, investigators compared genome sequencing with cytogenetic analysis in 263 patients with acute myeloid leukemia or myelodysplastic syndromes. Prospective sequencing detected new genetic information that was not revealed by cytogenetic analysis in nearly 25% of the patients, which altered the risk category for most of these patients.

To correlate the variable clinical features of oestrogen-receptor-positive breast cancer with somatic alterations, we studied pretreatment tumour biopsies accrued from patients in two studies of neoadjuvant aromatase inhibitor therapy by massively parallel sequencing and analysis. Eighteen significantly mutated genes were identified, including five genes ( RUNX1 , CBFB , MYH9 , MLL3 and SF3B1 ) previously linked to haematopoietic disorders. Mutant MAP3K1 was associated with luminal A status, low-grade histology and low proliferation rates, whereas mutant TP53 was associated with the opposite pattern. Moreover, mutant GATA3 correlated with suppression of proliferation upon aromatase inhibitor treatment. Pathway analysis demonstrated that mutations in MAP2K4 , a MAP3K1 substrate, produced similar perturbations as MAP3K1 loss. Distinct phenotypes in oestrogen-receptor-positive breast cancer are associated with specific patterns of somatic mutations that map into cellular pathways linked to tumour biology, but most recurrent mutations are relatively infrequent. Prospective clinical trials based on these findings will require comprehensive genome sequencing. Whole-genome analysis of oestrogen-receptor-positive tumours in patients treated with aromatase inhibitors show that distinct phenotypes are associated with specific patterns of somatic mutations; however, most recurrent mutations are relatively infrequent so prospective clinical trials will require comprehensive sequencing and large study populations. Tumour responsiveness to aromatase inhibitors Elaine Mardis and colleagues use whole-genome sequencing to gain insight into the mutational landscape of tissue samples from patients with oestrogen-receptor-positive (ER+) breast cancer treated with a neoadjuvant aromatase inhibitor. They identify a number of disease-linked mutations that specifically correlate with tumour-cell histology, proliferation rates and response to treatment. Such information could be used to determine which patients will benefit from aromatase-inhibitor therapy.

A comparison of the genomic sequence of a tumor sample from a patient with acute myeloid leukemia (AML) and that of a normal skin sample from the same patient revealed an estimated 750 somatic mutations, of which 12 were in the coding sequences of genes and 52 were in conserved regions or regions with regulatory potential. Four mutations were found to be recurrent in AML, including mutations in NRAS, NPM1, IDH1, and a conserved region on chromosome 10. A comparison of the genomic sequence of a tumor sample from a patient with acute myeloid leukemia (AML) and that of a normal skin sample from the same patient revealed an estimated 750 somatic mutations. Four mutations were found to be recurrent in AML. Acute myeloid leukemia (AML) is a clonal hematopoietic disease caused by both inherited and acquired genetic alterations. 1 – 3 Current AML classification and prognostic systems incorporate genetic information but are limited to known abnormalities that have previously been identified with the use of cytogenetics, array comparative genomic hybridization (CGH), gene-expression profiling, and the resequencing of candidate genes (see the Glossary). The karyotyping of AML cells remains the most powerful predictor of the outcome in patients with AML and is routinely used by clinicians. 4 , 5 As an adjunct to cytogenetic studies, small subcytogenetic amplifications and deletions can be identified with the use . . .

Massively parallel DNA sequencing technologies provide an unprecedented ability to screen entire genomes for genetic changes associated with tumour progression. Here we describe the genomic analyses of four DNA samples from an African-American patient with basal-like breast cancer: peripheral blood, the primary tumour, a brain metastasis and a xenograft derived from the primary tumour. The metastasis contained two de novo mutations and a large deletion not present in the primary tumour, and was significantly enriched for 20 shared mutations. The xenograft retained all primary tumour mutations and displayed a mutation enrichment pattern that resembled the metastasis. Two overlapping large deletions, encompassing CTNNA1 , were present in all three tumour samples. The differential mutation frequencies and structural variation patterns in metastasis and xenograft compared with the primary tumour indicate that secondary tumours may arise from a minority of cells within the primary tumour. Cancer progression genomics With the latest DNA sequencing technologies it is now possible to screen an entire genome for the genetic changes associated with tumour progression. This approach has been used to obtain complete sequences of four DNA samples from a 44-year-old African-American patient with basal-like breast cancer: the primary tumour, peripheral blood, a brain metastasis and a first-passage xenograft derived from the primary tumour. Mutational analysis suggests that the metastasis tumour specifically selects a subset of cells from the primary tumour that contain pre-existing mutations, and also develops a small number of de novo mutations. Massively parallel DNA sequencing allows entire genomes to be screened for genetic changes associated with tumour progression. Here, the genomes of four DNA samples from a 44-year-old African-American patient with basal-like breast cancer were analysed. The samples came from peripheral blood, the primary tumour, a brain metastasis and a xenograft derived from the primary tumour. The findings indicate that cells with a distinct subset of the primary tumour mutation might be selected during metastasis and xenografting.

Salmonella enterica subspecies I, serovar Typhimurium ( S. typhimurium ), is a leading cause of human gastroenteritis, and is used as a mouse model of human typhoid fever 1 . The incidence of non-typhoid salmonellosis is increasing worldwide 2 , 3 , 4 , causing millions of infections and many deaths in the human population each year. Here we sequenced the 4,857-kilobase (kb) chromosome and 94-kb virulence plasmid of S. typhimurium strain LT2. The distribution of close homologues of S. typhimurium LT2 genes in eight related enterobacteria was determined using previously completed genomes of three related bacteria, sample sequencing of both S. enterica serovar Paratyphi A ( S. paratyphi A) and Klebsiella pneumoniae , and hybridization of three unsequenced genomes to a microarray of S. typhimurium LT2 genes. Lateral transfer of genes is frequent, with 11% of the S. typhimurium LT2 genes missing from S. enterica serovar Typhi ( S. typhi ), and 29% missing from Escherichia coli K12. The 352 gene homologues of S. typhimurium LT2 confined to subspecies I of S. enterica —containing most mammalian and bird pathogens 5 —are useful for studies of epidemiology, host specificity and pathogenesis. Most of these homologues were previously unknown, and 50 may be exported to the periplasm or outer membrane, rendering them accessible as therapeutic or vaccine targets.

In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms.

The scarcity of labelled data is specifically an urgent challenge in the field of quantum machine learning (QML). Two transfer fusion frameworks are proposed in this paper to predict the labels of a target domain data by aligning its distribution to a different but related labelled source domain on quantum devices. The frameworks fuses the quantum data from two different, but related domains through a quantum information infusion channel. The predicting tasks in the target domain can be achieved with quantum advantages by post-processing quantum measurement results. One framework, the quantum basic linear algebra subroutines (QBLAS) based implementation, can theoretically achieve the procedure of transfer fusion with quadratic speedup on a universal quantum computer. In addition, the other framework, a hardware-scalable architecture, is implemented on the noisy intermediate-scale quantum (NISQ) devices through a variational hybrid quantum-classical procedure. Numerical experiments on the synthetic and handwritten digits datasets demonstrate that the variatioinal transfer fusion (TF) framework can reach state-of-the-art (SOTA) quantum DA method performance.