Chromosome-scale shotgun assembly using an in vitro method for long-range linkage.

Long-range and highly accurate de novo assembly from short-read data is one of the most pressing challenges in genomics. Recently, it has been shown that read pairs generated by proximity ligation of DNA in chromatin of living tissue can address this problem, dramatically increasing the scaffold contiguity of assemblies. Here, we describe a simpler approach ("Chicago") based on in vitro reconstituted chromatin. We generated two Chicago data sets with human DNA and developed a statistical model and a new software pipeline ("HiRise") that can identify poor quality joins and produce accurate, long-range sequence scaffolds. We used these to construct a highly accurate de novo assembly and scaffolding of a human genome with scaffold N50 of 20 Mbp. We also demonstrated the utility of Chicago for improving existing assemblies by reassembling and scaffolding the genome of the American alligator. With a single library and one lane of Illumina HiSeq sequencing, we increased the scaffold N50 of the American alligator from 508 kbp to 10 Mbp.

Machine learning enables detection of early-stage colorectal cancer by whole-genome sequencing of plasma cell-free DNA.

BACKGROUND: Blood-based methods using cell-free DNA (cfDNA) are under development as an alternative to existing screening tests. However, early-stage detection of cancer using tumor-derived cfDNA has proven challenging because of the small proportion of cfDNA derived from tumor tissue in early-stage disease. A machine learning approach to discover signatures in cfDNA, potentially reflective of both tumor and non-tumor contributions, may represent a promising direction for the early detection of cancer. METHODS: Whole-genome sequencing was performed on cfDNA extracted from plasma samples (N = 546 colorectal cancer and 271 non-cancer controls). Reads aligning to protein-coding gene bodies were extracted, and read counts were normalized. cfDNA tumor fraction was estimated using IchorCNA. Machine learning models were trained using k-fold cross-validation and confounder-based cross-validations to assess generalization performance. RESULTS: In a colorectal cancer cohort heavily weighted towards early-stage cancer (80% stage I/II), we achieved a mean AUC of 0.92 (95% CI 0.91-0.93) with a mean sensitivity of 85% (95% CI 83-86%) at 85% specificity. Sensitivity generally increased with tumor stage and increasing tumor fraction. Stratification by age, sequencing batch, and institution demonstrated the impact of these confounders and provided a more accurate assessment of generalization performance. CONCLUSIONS: A machine learning approach using cfDNA achieved high sensitivity and specificity in a large, predominantly early-stage, colorectal cancer cohort. The possibility of systematic technical and institution-specific biases warrants similar confounder analyses in other studies. Prospective validation of this machine learning method and evaluation of a multi-analyte approach are underway.

Renal systems biology of patients with systemic inflammatory response syndrome.

A systems biology approach was used to comprehensively examine the impact of renal disease and hemodialysis (HD) on patient response during critical illness. To achieve this, we examined the metabolome, proteome, and transcriptome of 150 patients with critical illness, stratified by renal function. Quantification of plasma metabolites indicated greater change as renal function declined, with the greatest derangements in patients receiving chronic HD. Specifically, 6 uremic retention molecules, 17 other protein catabolites, 7 modified nucleosides, and 7 pentose phosphate sugars increased as renal function declined, consistent with decreased excretion or increased catabolism of amino acids and ribonucleotides. Similarly, the proteome showed increased levels of low-molecular-weight proteins and acute-phase reactants. The transcriptome revealed a broad-based decrease in mRNA levels among patients on HD. Systems integration revealed an unrecognized association between plasma RNASE1 and several RNA catabolites and modified nucleosides. Further, allantoin, N1-methyl-4-pyridone-3-carboxamide, and N-acetylaspartate were inversely correlated with the majority of significantly downregulated genes. Thus, renal function broadly affected the plasma metabolome, proteome, and peripheral blood transcriptome during critical illness; changes were not effectively mitigated by hemodialysis. These studies allude to several novel mechanisms whereby renal dysfunction contributes to critical illness.

FLOWERING LOCUS T duplication coordinates reproductive and vegetative growth in perennial poplar.

Annual plants grow vegetatively at early developmental stages and then transition to the reproductive stage, followed by senescence in the same year. In contrast, after successive years of vegetative growth at early ages, woody perennial shoot meristems begin repeated transitions between vegetative and reproductive growth at sexual maturity. However, it is unknown how these repeated transitions occur without a developmental conflict between vegetative and reproductive growth. We report that functionally diverged paralogs FLOWERING LOCUS T1 (FT1) and FLOWERING LOCUS T2 (FT2), products of whole-genome duplication and homologs of Arabidopsis thaliana gene FLOWERING LOCUS T (FT), coordinate the repeated cycles of vegetative and reproductive growth in woody perennial poplar (Populus spp.). Our manipulative physiological and genetic experiments coupled with field studies, expression profiling, and network analysis reveal that reproductive onset is determined by FT1 in response to winter temperatures, whereas vegetative growth and inhibition of bud set are promoted by FT2 in response to warm temperatures and long days in the growing season. The basis for functional differentiation between FT1 and FT2 appears to be expression pattern shifts, changes in proteins, and divergence in gene regulatory networks. Thus, temporal separation of reproductive onset and vegetative growth into different seasons via FT1 and FT2 provides seasonality and demonstrates the evolution of a complex perennial adaptive trait after genome duplication.

Comparison of planning techniques when air/fluid is present using the strut-adjusted volume implant (SAVI) for HDR-based accelerated partial breast irradiation.

The presence of air/fluid surrounding implantable devices used for partial breast irradiation may significantly impact dose coverage to at-risk tissue. Of the 67 total patients retrospectively evaluated for this study, 32 (48%) had greater than 1 cc volume of air/fluid extending outside of the strut-adjusted volume implant (SAVI) device surface and were selected for comparison of planning approaches. The planning approaches utilized two different definitions of PTV_EVAL. One definition of a PTV_EVAL (PTV_EVALSAVI) was based on expanding 1 cm beyond the SAVI device only while accounting for the air/fluid using the NSABP Protocol B-39/RTOG Protocol 0413. The second PTV_EVAL definition (PTV_EVALCAV) was based on expanding 1 cm beyond the cavity (SAVI device plus air/fluid volume). The results indicate use of the B-39 formalism to account for air/fluid displacing the PTV_EVAL may overestimate the dose coverage to the at-risk tissue, especially for large contiguous volumes of air/fluid. Using the SAVI device to optimize dose covering the PTV_EVALCAV volume surrounding the cavity improves dosimetric coverage to at-risk tissue by 11.3% and 8.7% for V100 and V90, respectively, while the average V150 and V200 indices for PTV_EVALCAV increased by 9.1 cc and 5.0cc, respectively, and the average maximum rib and skin doses increased by 11.1% and 6.1%, respectively. The maximum skin dose, rib dose, V150, and V200 all met the planning objectives despite any increase in these parameters.

Genome sequencing and mapping reveal loss of heterozygosity as a mechanism for rapid adaptation in the vegetable pathogen Phytophthora capsici.

The oomycete vegetable pathogen Phytophthora capsici has shown remarkable adaptation to fungicides and new hosts. Like other members of this destructive genus, P. capsici has an explosive epidemiology, rapidly producing massive numbers of asexual spores on infected hosts. In addition, P. capsici can remain dormant for years as sexually recombined oospores, making it difficult to produce crops at infested sites, and allowing outcrossing populations to maintain significant genetic variation. Genome sequencing, development of a high-density genetic map, and integrative genomic or genetic characterization of P. capsici field isolates and intercross progeny revealed significant mitotic loss of heterozygosity (LOH) in diverse isolates. LOH was detected in clonally propagated field isolates and sexual progeny, cumulatively affecting >30% of the genome. LOH altered genotypes for more than 11,000 single-nucleotide variant sites and showed a strong association with changes in mating type and pathogenicity. Overall, it appears that LOH may provide a rapid mechanism for fixing alleles and may be an important component of adaptability for P. capsici.

Exploring Perceptions of Equine Welfare Scenarios Using a Positive Approach.

Horse welfare is a sensitive topic that often results in a variety of strong feelings when discussed in the horse-owning public. This study used a scenario-based questionnaire in a positive psychology approach to assess the public's feelings and discussions about horse welfare. Results indicated themes in important welfare qualities such as turnout, shelter, and ability to express natural behaviors, as well as a positive discussion about welfare. This study provides future implications for further research techniques in this area as well as communicative strategies surrounding equine welfare practices.

Fibrogenic and redox-related but not proinflammatory genes are upregulated in Lewis rat model of chronic silicosis.

Silicosis, a fibrotic granulomatous lung disease, may occur through accidental high-dose or occupational inhalation of silica, leading to acute/accelerated and chronic silicosis, respectively. While chronic silicosis has a long asymptomatic latency, lung inflammation and apoptosis are hallmarks of acute silicosis. In animal models, histiocytic granulomas develop within days after high-dose intratracheal (IT) silica instillation. However, following chronic inhalation of occupationally relevant doses of silica, discrete granulomas resembling human silicosis arise months after the final exposure without significant lung inflammation/apoptosis. To identify molecular events associated with chronic silicosis, lung RNA samples from controls or subchronic silica-exposed rats were analyzed by Affymetrix at 28 wk after silica exposures. Results suggested a significant upregulation of 144 genes and downregulation of 7 genes. The upregulated genes included complement cascade, chemokines/chemokine receptors, G-protein signaling components, metalloproteases, and genes associated with oxidative stress. To examine the kinetics of gene expression relevant to silicosis, quantitative polymerase chain reaction (qPCR), enzyme-linked immunosorbent assay (ELISA), Luminex-bead assays, Western blotting, and/or zymography were performed on lung tissues from 4 d, 28 wk, and intermediate times after subchronic silica exposure and compared with 14-d acute silicosis samples. Results indicated that genes regulating fibrosis (secreted phosphoprotein-1, Ccl2, and Ccl7), redox enzymes (superoxide dismutase-2 and arginase-1), and the enzymatic activities of matrix metalloproteinases 2 and 9 were upregulated in acute and chronic silicosis models. However, proinflammatory cytokines were strongly upregulated only in acute silicosis. Thus, inflammatory cytokines are associated with acute but not chronic silicosis. Data suggest that genes regulating fibrosis, oxidative stress, and metalloproteases may contribute to both acute and chronic silicosis.

Structural Variation Detection by Proximity Ligation from Formalin-Fixed, Paraffin-Embedded Tumor Tissue.

The clinical management and therapy of many solid tumor malignancies depends on detection of medically actionable or diagnostically relevant genetic variation. However, a principal challenge for genetic assays from tumors is the fragmented and chemically damaged state of DNA in formalin-fixed, paraffin-embedded (FFPE) samples. From highly fragmented DNA and RNA there is no current technology for generating long-range DNA sequence data as is required to detect genomic structural variation or long-range genotype phasing. We have developed a high-throughput chromosome conformation capture approach for FFPE samples that we call Fix-C, which is similar in concept to Hi-C. Fix-C enables structural variation detection from archival FFPE samples. This method was applied to 15 clinical adenocarcinoma- and sarcoma-positive control specimens spanning a broad range of tumor purities. In this panel, Fix-C analysis achieves a 90% concordance rate with fluorescence in situ hybridization assays, the current clinical gold standard. In addition, novel structural variation undetected by other methods could be identified, and long-range chromatin configuration information recovered from these FFPE samples harboring highly degraded DNA. This powerful approach will enable detailed resolution of global genome rearrangement events during cancer progression from FFPE material and will inform the development of targeted molecular diagnostic assays for patient care.

An integrated transcriptome and expressed variant analysis of sepsis survival and death.

BACKGROUND: Sepsis, a leading cause of morbidity and mortality, is not a homogeneous disease but rather a syndrome encompassing many heterogeneous pathophysiologies. Patient factors including genetics predispose to poor outcomes, though current clinical characterizations fail to identify those at greatest risk of progression and mortality. METHODS: The Community Acquired Pneumonia and Sepsis Outcome Diagnostic study enrolled 1,152 subjects with suspected sepsis. We sequenced peripheral blood RNA of 129 representative subjects with systemic inflammatory response syndrome (SIRS) or sepsis (SIRS due to infection), including 78 sepsis survivors and 28 sepsis non-survivors who had previously undergone plasma proteomic and metabolomic profiling. Gene expression differences were identified between sepsis survivors, sepsis non-survivors, and SIRS followed by gene enrichment pathway analysis. Expressed sequence variants were identified followed by testing for association with sepsis outcomes. RESULTS: The expression of 338 genes differed between subjects with SIRS and those with sepsis, primarily reflecting immune activation in sepsis. Expression of 1,238 genes differed with sepsis outcome: non-survivors had lower expression of many immune function-related genes. Functional genetic variants associated with sepsis mortality were sought based on a common disease-rare variant hypothesis. VPS9D1, whose expression was increased in sepsis survivors, had a higher burden of missense variants in sepsis survivors. The presence of variants was associated with altered expression of 3,799 genes, primarily reflecting Golgi and endosome biology. CONCLUSIONS: The activation of immune response-related genes seen in sepsis survivors was muted in sepsis non-survivors. The association of sepsis survival with a robust immune response and the presence of missense variants in VPS9D1 warrants replication and further functional studies. TRIAL REGISTRATION: ClinicalTrials.gov NCT00258869. Registered on 23 November 2005.

An integrated clinico-metabolomic model improves prediction of death in sepsis.

Sepsis is a common cause of death, but outcomes in individual patients are difficult to predict. Elucidating the molecular processes that differ between sepsis patients who survive and those who die may permit more appropriate treatments to be deployed. We examined the clinical features and the plasma metabolome and proteome of patients with and without community-acquired sepsis, upon their arrival at hospital emergency departments and 24 hours later. The metabolomes and proteomes of patients at hospital admittance who would ultimately die differed markedly from those of patients who would survive. The different profiles of proteins and metabolites clustered into the following groups: fatty acid transport and ß-oxidation, gluconeogenesis, and the citric acid cycle. They differed consistently among several sets of patients, and diverged more as death approached. In contrast, the metabolomes and proteomes of surviving patients with mild sepsis did not differ from survivors with severe sepsis or septic shock. An algorithm derived from clinical features together with measurements of five metabolites predicted patient survival. This algorithm may help to guide the treatment of individual patients with sepsis.

The chemokine CCL2 increases prostate tumor growth and bone metastasis through macrophage and osteoclast recruitment.

CC chemokine ligand 2 (CCL2, also known as monocyte chemoattractant protein-1) has been demonstrated to recruit monocytes to tumor sites. Monocytes are capable of being differentiated into tumor-associated macrophages (TAMs) and osteoclasts (OCs). TAMs have been shown to promote tumor growth in several cancer types. Osteoclasts have also been known to play an important role in cancer bone metastasis. To investigate the effects of CCL2 on tumorigenesis and its potential effects on bone metastasis of human prostate cancer, CCL2 was overexpressed into a luciferase-tagged human prostate cancer cell line PC-3. In vitro, the conditioned medium of CCL2 overexpressing PC-3luc cells (PC-3(lucCCL2)) was a potent chemoattractant for mouse monocytes in comparison to a conditioned medium from PC-3(lucMock). In addition, CCL2 overexpression increased the growth of transplanted xenografts and increased the accumulation of macrophages in vivo. In a tumor dissemination model, PC-3(lucCCL2) enhanced the growth of bone metastasis, which was associated with more functional OCs. Neutralizing antibodies targeting both human and mouse CCL2 inhibited the growth of PC-3(luc), which was accompanied by a decrease in macrophage recruitment to the tumor. These findings suggest that CCL2 increases tumor growth and bone metastasis through recruitment of macrophages and OCs to the tumor site.