Search for: All records

SUMMARY Self‐incompatibility inPetuniais controlled by the polymorphicS‐locus, which containsS‐RNaseencoding the pistil determinant and 16–20S‐locus F‐box(SLF) genes collectively encoding the pollen determinant. Here we sequenced and assembled approximately 3.1 Mb of theS₂‐haplotype of theS‐locus inPetunia inflatausing bacterial artificial chromosome clones collectively containing all 17SLFgenes,SLFLike1, andS‐RNase. TwoSLFpseudogenes and 28 potential protein‐coding genes were identified, 20 of which were also found at theS‐loci of both theS_6a‐haplotype ofP. inflataand theS_N‐haplotype of self‐compatiblePetunia axillaris, but not in theS‐locus remnants of self‐compatible potato (Solanum tuberosum) and tomato (Solanum lycopersicum). Comparative analyses ofS‐locus sequences of these threeS‐haplotypes revealed potential genetic exchange in the flanking regions ofSLFgenes, resulting in highly similar flanking regions between different types ofSLFand between alleles of the same type ofSLFof differentS‐haplotypes. The high degree of sequence similarity in the flanking regions could often be explained by the presence of similar long terminal repeat retroelements, which were enriched at theS‐loci of all threeS‐haplotypes and in the flanking regions of allS‐locus genes examined. We also found evidence of the association of transposable elements withSLFpseudogenes. Based on the hypothesis thatSLFgenes were derived by retrotransposition, we identified 10F‐boxgenes as putativeSLFparent genes. Our results shed light on the importance of non‐coding sequences in the evolution of theS‐locus, and on possible evolutionary mechanisms of generation, proliferation, and deletion ofSLFgenes. 

Abstract Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb -1 at  √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.