Continental growth histories revealed by detrital zircon trace elements: a case study from India

published_or_final_versio

Universal corrections to entanglement entropy of local quantum quenches

We study the time evolution of single interval Renyi and entanglement entropies following local quantum quenches in two dimensional conformal field theories at finite temperature for which the locally excited states have a finite temporal width, \epsilon. We show that, for local quenches produced by the action of a conformal primary field, the time dependence of Renyi and entanglement entropies at order \epsilon^2 is universal. It is determined by the expectation value of the stress tensor in the replica geometry and proportional to the conformal dimension of the primary field generating the local excitation. We also show that in CFTs with a gravity dual, the \epsilon^2 correction to the holographic entanglement entropy following a local quench precisely agrees with the CFT prediction. We then consider CFTs admitting a higher spin symmetry and turn on a higher spin chemical potential \mu. We calculate the time dependence of the order \epsilon^2 correction to the entanglement entropy for small \mu, and show that the contribution at order \mu^2 is universal. We verify our arguments against exact results for minimal models and the free fermion theory

An analysis of single amino acid repeats as use case for application specific background models

Background Sequence analysis aims to identify biologically relevant signals against a backdrop of functionally meaningless variation. Increasingly, it is recognized that the quality of the background model directly affects the performance of analyses. State-of-the-art approaches rely on classical sequence models that are adapted to the studied dataset. Although performing well in the analysis of globular protein domains, these models break down in regions of stronger compositional bias or low complexity. While these regions are typically filtered, there is increasing anecdotal evidence of functional roles. This motivates an exploration of more complex sequence models and application-specific approaches for the investigation of biased regions. Results Traditional Markov-chains and application-specific regression models are compared using the example of predicting runs of single amino acids, a particularly simple class of biased regions. Cross-fold validation experiments reveal that the alternative regression models capture the multi-variate trends well, despite their low dimensionality and in contrast even to higher-order Markov-predictors. We show how the significance of unusual observations can be computed for such empirical models. The power of a dedicated model in the detection of biologically interesting signals is then demonstrated in an analysis identifying the unexpected enrichment of contiguous leucine-repeats in signal-peptides. Considering different reference sets, we show how the question examined actually defines what constitutes the 'background'. Results can thus be highly sensitive to the choice of appropriate model training sets. Conversely, the choice of reference data determines the questions that can be investigated in an analysis. Conclusions Using a specific case of studying biased regions as an example, we have demonstrated that the construction of application-specific background models is both necessary and feasible in a challenging sequence analysis situation

HtrA2/Omi Terminates Cytomegalovirus Infection and Is Controlled by the Viral Mitochondrial Inhibitor of Apoptosis (vMIA)

Viruses encode suppressors of cell death to block intrinsic and extrinsic host-initiated death pathways that reduce viral yield as well as control the termination of infection. Cytomegalovirus (CMV) infection terminates by a caspase-independent cell fragmentation process after an extended period of continuous virus production. The viral mitochondria-localized inhibitor of apoptosis (vMIA; a product of the UL37x1 gene) controls this fragmentation process. UL37x1 mutant virus-infected cells fragment three to four days earlier than cells infected with wt virus. Here, we demonstrate that infected cell death is dependent on serine proteases. We identify mitochondrial serine protease HtrA2/Omi as the initiator of this caspase-independent death pathway. Infected fibroblasts develop susceptibility to death as levels of mitochondria-resident HtrA2/Omi protease increase. Cell death is suppressed by the serine protease inhibitor TLCK as well as by the HtrA2-specific inhibitor UCF-101. Experimental overexpression of HtrA2/Omi, but not a catalytic site mutant of the enzyme, sensitizes infected cells to death that can be blocked by vMIA or protease inhibitors. Uninfected cells are completely resistant to HtrA2/Omi induced death. Thus, in addition to suppression of apoptosis and autophagy, vMIA naturally controls a novel serine protease-dependent CMV-infected cell-specific programmed cell death (cmvPCD) pathway that terminates the CMV replication cycle

Surface and Temporal Biosignatures

Recent discoveries of potentially habitable exoplanets have ignited the prospect of spectroscopic investigations of exoplanet surfaces and atmospheres for signs of life. This chapter provides an overview of potential surface and temporal exoplanet biosignatures, reviewing Earth analogues and proposed applications based on observations and models. The vegetation red-edge (VRE) remains the most well-studied surface biosignature. Extensions of the VRE, spectral "edges" produced in part by photosynthetic or nonphotosynthetic pigments, may likewise present potential evidence of life. Polarization signatures have the capacity to discriminate between biotic and abiotic "edge" features in the face of false positives from band-gap generating material. Temporal biosignatures -- modulations in measurable quantities such as gas abundances (e.g., CO2), surface features, or emission of light (e.g., fluorescence, bioluminescence) that can be directly linked to the actions of a biosphere -- are in general less well studied than surface or gaseous biosignatures. However, remote observations of Earth's biosphere nonetheless provide proofs of concept for these techniques and are reviewed here. Surface and temporal biosignatures provide complementary information to gaseous biosignatures, and while likely more challenging to observe, would contribute information inaccessible from study of the time-averaged atmospheric composition alone

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Allelic relationships of flowering time genes in chickpea

Flowering time and crop duration are the most important traits for adaptation of chickpea (Cicer arietinum L.) to different agro-climatic conditions. Early flowering and early maturity enhance adaptation of chickpea to short season environments. This study was conducted to establish allelic relationships of the early flowering genes of ICC 16641, ICC 16644 and ICCV 96029 with three known early flowering genes, efl-1 (ICCV 2), ppd or efl-2 (ICC 5810), and efl-3 (BGD 132). In all cases, late flowering was dominant to early-flowering. The results indicated that the efl-1 gene identified from ICCV 2 was also present in ICCV 96029, which has ICCV 2 as one of the parents in its pedigree. ICC 16641 and ICC 16644 had a common early flowering gene which was not allelic to other reported early flowering genes. The new early flowering gene was designated efl-4. In most of the crosses, days to flowering was positively correlated with days to maturity, number of pods per plant, number of seeds per plant and seed yield per plant and negatively correlated or had no correlation with 100-seed weight. The double-pod trait improved grain yield per plant in the crosses where it delayed maturity. The information on allelic relationships of early flowering genes and their effects on yield and yield components will be useful in chickpea breeding for desired phenology

Inheritance and relationships of flowering time and seed size in kabuli chickpea

Flowering time and seed size are the important traits for adaptation in chickpea. Early phenology (time of flowering, podding and maturity) enhance chickpea adaptation to short season environments. Along with a trait of consumer preference, seed size has also been considered as an important factor for subsequent plant growth parameters including germination, seedling vigour and seedling mass. Small seeded kabuli genotype ICC 16644 was crossed with four genotypes (JGK 2, KAK 2, KRIPA and ICC 17109) to study inheritance of flowering time and seed size. The relationships of phenology with seed size, grain yield and its component traits were studied. The study included parents, F1, F2 and F3 of four crosses. The segregation data of F2 indicated flowering time in chickpea was governed by two genes with duplicate recessive epistasis and lateness was dominant to earliness. Two genes were controlling 100-seed weight where small seed size was dominant over large seed size. Early phenology had significant negative or no association (ICC 16644 × ICC 17109) with 100-seed weight. Yield per plant had significant positive association with number of seeds per plant, number of pods per plant, biological yield per plant, 100-seed weight, harvest index and plant height and hence could be considered as factors for seed yield improvement. Phenology had no correlation with yield per se (seed yield per plant) in any of the crosses studied. Thus, present study shows that in certain genetic background it might be possible to breed early flowering genotypes with large seed size in chickpea and selection of early flowering genotypes may not essentially have a yield penalty

A genome-scale integrated approach aids in genetic dissection of complex flowering time trait in chickpea

A combinatorial approach of candidate gene-based association analysis and genome-wide association study (GWAS) integrated with QTL mapping, differential gene expression profiling and molecular haplotyping was deployed in the present study for quantitative dissection of complex flowering time trait in chickpea. Candidate gene-based association mapping in a flowering time association panel (92 diverse desi and kabuli accessions) was performed by employing the genotyping information of 5724 SNPs discovered from 82 known flowering chickpea gene orthologs of Arabidopsis and legumes as well as 832 gene-encoding transcripts that are differentially expressed during flower development in chickpea. GWAS using both genome-wide GBS- and candidate gene-based genotyping data of 30,129 SNPs in a structured population of 92 sequenced accessions (with 200–250 kb LD decay) detected eight maximum effect genomic SNP loci (genes) associated (34 % combined PVE) with flowering time. Six flowering time-associated major genomic loci harbouring five robust QTLs mapped on a high-resolution intra-specific genetic linkage map were validated (11.6–27.3 % PVE at 5.4–11.7 LOD) further by traditional QTL mapping. The flower-specific expression, including differential up- and down-regulation (>three folds) of eight flowering time-associated genes (including six genes validated by QTL mapping) especially in early flowering than late flowering contrasting chickpea accessions/mapping individuals during flower development was evident. The gene haplotype-based LD mapping discovered diverse novel natural allelic variants and haplotypes in eight genes with high trait association potential (41 % combined PVE) for flowering time differentiation in cultivated and wild chickpea. Taken together, eight potential known/candidate flowering time-regulating genes [efl1 (early flowering 1), FLD (Flowering locus D), GI (GIGANTEA), Myb (Myeloblastosis), SFH3 (SEC14-like 3), bZIP (basic-leucine zipper), bHLH (basic helix-loop-helix) and SBP (SQUAMOSA promoter binding protein)], including novel markers, QTLs, alleles and haplotypes delineated by aforesaid genome-wide integrated approach have potential for marker-assisted genetic improvement and unravelling the domestication pattern of flowering time in chickpea

Chickpea

The narrow genetic base of cultivated chickpea warrants systematic collection, documentation and evaluation of chickpea germplasm and particularly wild Cicer species for effective and efficient use in chickpea breeding programmes. Limiting factors to crop production, possible solutions and ways to overcome them, importance of wild relatives and barriers to alien gene introgression and strategies to overcome them and traits for base broadening have been discussed. It has been clearly demonstrated that resistance to major biotic and abiotic stresses can be successfully introgressed from the primary gene pool comprising progenitor species. However, many desirable traits including high degree of resistance to multiple stresses that are present in the species belonging to secondary and tertiary gene pools can also be introgressed by using special techniques to overcome pre- and post-fertilization barriers. Besides resistance to various biotic and abiotic stresses, the yield QTLs have also been introgressed from wild Cicer species to cultivated varieties. Status and importance of molecular markers, genome mapping and genomic tools for chickpea improvement are elaborated. Because of major genes for various biotic and abiotic stresses, the transfer of agronomically important traits into elite cultivars has been made easy and practical through marker-assisted selection and marker-assisted backcross. The usefulness of molecular markers such as SSR and SNP for the construction of high-density genetic maps of chickpea and for the identification of genes/QTLs for stress resistance, quality and yield contributing traits has also been discussed