Application of genomic and quantitative genetic tools to identify candidate resistance genes for brown rot resistance in peach.

The availability of a complete peach genome assembly and three different peach genome sequences created by our group provide new opportunities for application of genomic data and can improve the power of the classical Quantitative Trait Loci (QTL) approaches to identify candidate genes for peach disease resistance. Brown rot caused by Monilinia spp., is the most important fungal disease of stone fruits worldwide. Improved levels of peach fruit rot resistance have been identified in some cultivars and advanced selections developed in the UC Davis and USDA breeding programs. Whole genome sequencing of the Pop-DF parents lead to discovery of high-quality SNP markers for QTL genome scanning in this experimental population. Pop-DF created by crossing a brown rot moderately resistant cultivar 'Dr. Davis' and a brown rot resistant introgression line, 'F8,1-42', derived from an initial almond × peach interspecific hybrid, was evaluated for brown rot resistance in fruit of harvest maturity over three seasons. Using the SNP linkage map of Pop-DF and phenotypic data collected with inoculated fruit, a genome scan for QTL identified several SNP markers associated with brown rot resistance. Two of these QTLs were placed on linkage group 1, covering a large (physical) region on chromosome 1. The genome scan for QTL and SNP effects predicted several candidate genes associated with disease resistance responses in other host-pathogen systems. Two potential candidate genes, ppa011763m and ppa026453m, may be the genes primarily responsible for M. fructicola recognition in peach, activating both PAMP-triggered immunity (PTI) and effector-triggered immunity (ETI) responses. Our results provide a foundation for further genetic dissection, marker assisted breeding for brown rot resistance, and development of peach cultivars resistant to brown rot

In vivo assessment of interictal sarcolemmal membrane properties in hypokalaemic and hyperkalaemic periodic paralysis

OBJECTIVE: Hypokalaemic periodic paralysis (HypoPP) is caused by mutations of Cav1.1, and Na_{v}1.4 which result in an aberrant gating pore current. Hyperkalaemic periodic paralysis (HyperPP) is due to a gain-of-function mutation of the main alpha pore of Nav1.4. This study used muscle velocity recovery cycles (MVRCs) to investigate changes in interictal muscle membrane properties in vivo. METHODS: MVRCs and responses to trains of stimuli were recorded in tibialis anterior and compared in patients with HyperPP(n = 7), HypoPP (n = 10), and normal controls (n = 26). RESULTS: Muscle relative refractory period was increased, and early supernormality reduced in HypoPP, consistent with depolarisation of the interictal resting membrane potential. In HyperPP the mean supernormality and residual supernormality to multiple conditioning stimuli were increased, consistent with increased inward sodium current and delayed repolarisation, predisposing to spontaneous myotonic discharges. CONCLUSIONS: The in vivo findings suggest the interictal resting membrane potential is depolarized in HypoPP, and mostly normal in HyperPP. The MVRC findings in HyperPP are consistent with presence of a window current, previously proposed on the basis of in vitro expression studies. Although clinically similar, HyperPP was electrophysiologically distinct from paramyotonia congenita. SIGNIFICANCE: MVRCs provide important in vivo data that complements expression studies of ion channel mutations

Array-conditioned deconvolution of multiple component teleseismic recordings

We investigate the applicability of an array-conditioned deconvolution technique, developed for analyzing borehole seismic exploration data, to teleseismic receiver functions and data preprocessing steps for scattered wavefield imaging. This multichannel deconvolution technique constructs an approximate inverse filter to the estimated source signature by solving an overdetermined set of deconvolution equations, using an array of receivers detecting a common source. We find that this technique improves the efficiency and automation of receiverfunction calculation and data preprocessing workflow. We apply this technique to synthetic experiments and to teleseismic data recorded in a dense array in northern Canada. Our results show that this optimal deconvolution automatically determines and subsequently attenuates the noise from data, enhancing P-to-S converted phases in seismograms with various noise levels. In this context, the array-conditioned deconvolution presents a new, effective and automatic means for processing large amounts of array data, as it does not require any ad-hoc regularization; the regularization is achieved naturally by using the noise present in the array itself