Genomic prediction in hybrid breeding: I. Optimizing the training set design.

KEY MESSAGE: Training sets produced by maximizing the number of parent lines, each involved in one cross, had the highest prediction accuracy for H0 hybrids, but lowest for H1 and H2 hybrids. Genomic prediction holds great promise for hybrid breeding but optimum composition of the training set (TS) as determined by the number of parents (nTS) and crosses per parent (c) has received little attention. Our objective was to examine prediction accuracy ([Formula: see text]) of GCA for lines used as parents of the TS (I1 lines) or not (I0 lines), and H0, H1 and H2 hybrids, comprising crosses of type I0 × I0, I1 × I0 and I1 × I1, respectively, as function of nTS and c. In the theory, we developed estimates for [Formula: see text] of GBLUPs for hybrids: (i)[Formula: see text] based on the expected prediction accuracy, and (ii) [Formula: see text] based on [Formula: see text] of GBLUPs of GCA and SCA effects. In the simulation part, hybrid populations were generated using molecular data from two experimental maize data sets. Additive and dominance effects of QTL borrowed from literature were used to simulate six scenarios of traits differing in the proportion (τSCA = 1%, 6%, 22%) of SCA variance in σG2 and heritability (h2 = 0.4, 0.8). Values of [Formula: see text] and [Formula: see text] closely agreed with [Formula: see text] for hybrids. For given size NTS = nTS × c of TS, [Formula: see text] of H0 hybrids and GCA of I0 lines was highest for c = 1. Conversely, for GCA of I1 lines and H1 and H2 hybrids, c = 1 yielded lowest [Formula: see text] with concordant results across all scenarios for both data sets. In view of these opposite trends, the optimum choice of c for maximizing selection response across all types of hybrids depends on the size and resources of the breeding program.

Spontaneous and action potential-evoked Ca2+ release from endoplasmic reticulum in neocortical synaptic boutons.

Although the endoplasmic reticulum (ER) is present throughout axons, and IP3 and ryanodine receptors are widely expressed in nerve terminals, whether Ca2+ release from presynaptic stores contributes to action potential (AP)-evoked Ca2+ transients remains controversial. We investigated the release of Ca2+ from ER stores in boutons en passant of neocortical layer 5 pyramidal neurons. A hallmark of these stores is that they spontaneously release Ca2+ at a low frequency. Using a high-affinity Ca2+ indicator, we documented and characterised such spontaneous Ca2+ transients (sCaTs), which occurred at a rate of ~0.2 per min and raised the intracellular Ca2+ concentration ([Ca2+]i) by ~2 µM in the absence of exogenous buffers. Caffeine increased the average frequency of sCaTs by 90%, without affecting their amplitude and decay kinetics. Therefore, presynaptic ryanodine receptors were likely involved. To determine if presynaptic ER stores contribute to intracellular Ca2+ accumulation during repetitive stimulation, we measured [Ca2+]i during 2 s long trains of APs evoked at 10-50 Hz. We found that for frequencies <20 Hz, [Ca2+]i reached a steady state within ~500 ms after stimulation onset. However, for higher frequencies, [Ca2+]i continued to increase with AP number, suggesting that the rate of Ca2+ entry exceeded the rate of clearance. Comparison between measured and predicted values indicates supralinear summation of Ca2+. Block of the sarco/endoplasmic reticulum Ca2+-ATPase reduced the supralinearity of summation, without reducing the amplitude of a single AP-evoked Ca2+ transient. Together, our results implicate presynaptic ER stores as a source of Ca2+ during repetitive stimulation.

Serotonergic Modulation of Spontaneous and Evoked Transmitter Release in Layer II Pyramidal Cells of Rat Somatosensory Cortex.

As axons from the raphe nuclei densely innervate the somatosensory cortex, we investigated how serotonin (5-HT) modulates transmitter release in layer II pyramidal cells of rat barrel cortex. In the presence of tetrodotoxin and gabazine, 10 µM 5-HT caused a waxing and waning in the frequency of miniature excitatory postsynaptic currents (mEPSC) with no effect on amplitude. Specifically, within 15 min of recording the mEPSC frequency initially increased by 28 ± 7%, then dropped to below control (-15 ± 3%), before resurging back to 27 ± 7% larger than control. These changes were seen in 47% of pyramidal cells (responders) and were mediated by 5-HT2C receptors (5-HT2CR). Waxing resulted from phospholipase C activation, IP3 production, and Ca2+ release from presynaptic stores. Waning was prevented if PKC was blocked. In contrast, in paired recordings, the unitary EPSC amplitude was reduced by 50 ± 3% after 5-HT exposure in almost all cases with no significant effect on paired-pulse ratio and synaptic dynamics. This sustained EPSC reduction was also caused by 5-HT2R, but was mediated by presynaptic Gßγ subunits likely limiting influx through CaV2 channels. EPSC reduction, together with enhanced spontaneous noise in a restricted subset of inputs, could temporarily diminish the signal-to-noise ratio and affect the computation in the neocortical microcircuit.

Noradrenaline Increases mEPSC Frequency in Pyramidal Cells in Layer II of Rat Barrel Cortex via Calcium Release From Presynaptic Stores.

Somatosensory cortex is innervated by afferents originating from the locus coeruleus which typically release noradrenaline. We tested if activation of presynaptic α1-adrenoceptors (AR) coupled to a Gq-mediated signaling cascade resulted in calcium (Ca2+) release from stores and thereby increased spontaneous transmitter release in rat barrel cortex. Adding 1-100 µM noradrenaline (NA) or 5 µM cirazoline (CO), a α1-AR specific agonist, to the standard artificial cerebrospinal fluid increased the frequency of miniature excitatory postsynaptic currents (mEPSC) by 64 ± 7% in 51% of pyramidal cells in layer II (responders) with no effect on the amplitude. In 42 responders, the mEPSC frequency during control was significantly smaller (39 ± 2 vs. 53 ± 4 Hz) and upon NA exposure, the input resistance (Rin) decreased (9 ± 7%) compared to non-responders. Experiments using CO and the antagonist prazosin revealed that NA acted via binding to α1-ARs, which was further corroborated by simultaneously blocking ß- and α2-ARs with propranolol and yohimbine, which did not prevent the increase in mEPSC frequency. To verify elements in the signaling cascade, both the phospholipase C inhibitor edelfosine and the membrane permeable IP3 receptor blocker 2-APB averted the increase in mEPSC frequency. Likewise, emptying Ca2+ stores with cyclopiazonic acid or the chelation of intracellular Ca2+ with BAPTA-AM prevented the frequency increase, suggesting that the frequency increase was caused by presynaptic store release. When group I metabotropic glutamate receptors were activated with DHPG, co-application of NA occluded a further frequency increase suggesting that the two receptor activations may not signal independently of each other. The increased mEPSC frequency in a subset of pyramidal cells results in enhanced synaptic noise, which, together with the reduction in Rin, will affect computation in the network.

Diffusion of Ca2+ from Small Boutons en Passant into the Axon Shapes AP-Evoked Ca2+ Transients.

Not only the amplitude but also the time course of a presynaptic Ca2+ transient determine multiple aspects of synaptic transmission. In small bouton-type synapses, the mechanisms underlying the Ca2+ decay kinetics have not been fully investigated. Here, factors that shape an action-potential-evoked Ca2+ transient were quantitatively studied in synaptic boutons of neocortical layer 5 pyramidal neurons. Ca2+ transients were measured with different concentrations of fluorescent Ca2+ indicators and analyzed based on a single-compartment model. We found a small endogenous Ca2+-binding ratio (7 ± 2) and a high activity of Ca2+ transporters (0.64 ± 0.03 ms-1), both of which enable rapid clearance of Ca2+ from the boutons. However, contrary to predictions of the single-compartment model, the decay time course of the measured Ca2+ transients was biexponential and became prolonged during repetitive stimulation. Measurements of [Ca2+]i along the adjoining axon, together with an experimentally constrained model, showed that the initial fast decay of the Ca2+ transients predominantly arose from the diffusion of Ca2+ from the boutons into the axon. Therefore, for small boutons en passant, factors like terminal volume, axon diameter, and the concentration of mobile Ca2+-binding molecules are critical determinants of Ca2+ dynamics and thus Ca2+-dependent processes, including short-term synaptic plasticity.

An improved measurement of the Ca2+-binding affinity of fluorescent Ca2+ indicators.

Fluorescent Ca2+ indicators are widely used to measure the intracellular Ca2+ concentration ([Ca2+]i) in living cells, including neurons. By calibrating an indicator in solutions that mimic the main ionic constituents of the actual cytoplasm, [Ca2+]i can be determined from the measured fluorescence intensity. However, different studies have reported considerably different Ca2+-binding affinities (Kd) for the same indicator, even though they used calibrating solutions with similar compositions. In this paper, we present a method to accurately determine the Kd values of non-ratiometric Ca2+ indicators in solutions that mimicked a standard patch-clamp internal solution. The free Ca2+ concentration ([Ca2+]) in these solutions, which was set by either EGTA or HEDTA, was measured with a Ca2+-selective macroelectrode. We found that such a measurement was critical for an accurate calibration of the Ca2+ indicators. The Kd values of OGB-1, OGB-6F, fluo-5F, and fluo-4FF were 0.26 ±â€¯0.01, 8.7 ±â€¯0.4, 1.00 ±â€¯0.05, and 23.0 ±â€¯0.7 µM, respectively. Calculating [Ca2+] with Maxchelator, a widely used computer program, led to a significant underestimation of the Kd values of OGB-6F, fluo-5F, and fluo-4FF. This is because the purity of EGTA was considerably less than that advertised by the manufacturer. In addition, the Kd value of HEDTA was overestimated by Maxchelator. Therefore, besides batch-to-batch variations, the fact that [Ca2+] in the calibrating solutions of many studies was estimated with Maxchelator is very likely a reason for the different published values of Kd of Ca2+ indicators. Using a reaction-diffusion model to reproduce Ca2+ rises in a nerve terminal, we further showed that incorrect calibration of fluorescent Ca2+ indicators can underlie the large variation of the endogenous Ca2+ binding ratio between different types of excitatory synapses.

Short communication: Genomic prediction using imputed whole-genome sequence variants in Brown Swiss Cattle.

The accuracy of genomic prediction determines response to selection. It has been hypothesized that accuracy of genomic breeding values can be increased by a higher density of variants. We used imputed whole-genome sequence data and various single nucleotide polymorphism (SNP) selection criteria to estimate genomic breeding values in Brown Swiss cattle. The extreme scenarios were 50K SNP chip data and whole-genome sequence data with intermediate scenarios using linkage disequilibrium-pruned whole-genome sequence variants, only variants predicted to be missense, or the top 50K variants from genome-wide association studies. We estimated genomic breeding values for 3 traits (somatic cell score, nonreturn rate in heifers, and stature) and found differences in accuracy levels between traits. However, among different SNP sets, accuracy was very similar. In our analyses, sequence data led to a marginal increase in accuracy for 1 trait and was lower than 50K for the other traits. We concluded that the inclusion of imputed whole-genome sequence data does not lead to increased accuracy of genomic prediction with the methods.

Highly accurate sequence imputation enables precise QTL mapping in Brown Swiss cattle.

BACKGROUND: Within the last few years a large amount of genomic information has become available in cattle. Densities of genomic information vary from a few thousand variants up to whole genome sequence information. In order to combine genomic information from different sources and infer genotypes for a common set of variants, genotype imputation is required. RESULTS: In this study we evaluated the accuracy of imputation from high density chips to whole genome sequence data in Brown Swiss cattle. Using four popular imputation programs (Beagle, FImpute, Impute2, Minimac) and various compositions of reference panels, the accuracy of the imputed sequence variant genotypes was high and differences between the programs and scenarios were small. We imputed sequence variant genotypes for more than 1600 Brown Swiss bulls and performed genome-wide association studies for milk fat percentage at two stages of lactation. We found one and three quantitative trait loci for early and late lactation fat content, respectively. Known causal variants that were imputed from the sequenced reference panel were among the most significantly associated variants of the genome-wide association study. CONCLUSIONS: Our study demonstrates that whole-genome sequence information can be imputed at high accuracy in cattle populations. Using imputed sequence variant genotypes in genome-wide association studies may facilitate causal variant detection.

Genome-wide association studies of fertility and calving traits in Brown Swiss cattle using imputed whole-genome sequences.

BACKGROUND: The detection of quantitative trait loci has accelerated with recent developments in genomics. The introduction of genomic selection in combination with sequencing efforts has made a large amount of genotypic data available. Functional traits such as fertility and calving traits have been included in routine genomic estimation of breeding values making large quantities of phenotypic data available for these traits. This data was used to investigate the genetics underlying fertility and calving traits and to identify potentially causative genomic regions and variants. We performed genome-wide association studies for 13 functional traits related to female fertility as well as for direct and maternal calving ease based on imputed whole-genome sequences. Deregressed breeding values from ~1000-5000 bulls per trait were used to test for associations with approximately 10 million imputed sequence SNPs. RESULTS: We identified a QTL on BTA17 associated with non-return rate at 56 days and with interval from first to last insemination. We found two significantly associated non-synonymous SNPs within this QTL region. Two more QTL for fertility traits were identified on BTA25 and 29. A single QTL was identified for maternal calving traits on BTA13 whereas three QTL on BTA19, 21 and 25 were identified for direct calving traits. The QTL on BTA19 co-localizes with the reported BH2 haplotype. The QTL on BTA25 is concordant for fertility and calving traits and co-localizes with a QTL previously reported to influence stature and related traits in Brown Swiss dairy cattle. CONCLUSION: The detection of QTL and their causative variants remains challenging. Combining comprehensive phenotypic data with imputed whole genome sequences seems promising. We present a QTL on BTA17 for female fertility in dairy cattle with two significantly associated non-synonymous SNPs, along with five additional QTL for fertility traits and calving traits. For all of these we fine mapped the regions and suggest candidate genes and candidate variants.

Population structure and genomic inbreeding in nine Swiss dairy cattle populations.

BACKGROUND: Domestication, breed formation and intensive selection have resulted in divergent cattle breeds that likely exhibit their own genomic signatures. In this study, we used genotypes from 27,612 autosomal single nucleotide polymorphisms to characterize population structure based on 9214 sires representing nine Swiss dairy cattle populations: Brown Swiss (BS), Braunvieh (BV), Original Braunvieh (OB), Holstein (HO), Red Holstein (RH), Swiss Fleckvieh (SF), Simmental (SI), Eringer (ER) and Evolèner (EV). Genomic inbreeding (F ROH) and signatures of selection were determined by calculating runs of homozygosity (ROH). The results build the basis for a better understanding of the genetic development of Swiss dairy cattle populations and highlight differences between the original populations (i.e. OB, SI, ER and EV) and those that have become more popular in Switzerland as currently reflected by their larger populations (i.e. BS, BV, HO, RH and SF). RESULTS: The levels of genetic diversity were highest and lowest in the SF and BS breeds, respectively. Based on F ST values, we conclude that, among all pairwise comparisons, BS and HO (0.156) differ more than the other pairs of populations. The original Swiss cattle populations OB, SI, ER, and EV are clearly genetically separated from the Swiss cattle populations that are now more common and represented by larger numbers of cows. Mean levels of F ROH ranged from 0.027 (ER) to 0.091 (BS). Three of the original Swiss cattle populations, ER (F ROH: 0.027), OB (F ROH: 0.029), and SI (F ROH: 0.039), showed low levels of genomic inbreeding, whereas it was much higher in EV (F ROH: 0.074). Private signatures of selection for the original Swiss cattle populations are reported for BTA4, 5, 11 and 26. CONCLUSIONS: The low levels of genomic inbreeding observed in the original Swiss cattle populations ER, OB and SI compared to the other breeds are explained by a lesser use of artificial insemination and greater use of natural service. Natural service results in more sires having progeny at each generation and thus this breeding practice is likely the major reason for the remarkable levels of genetic diversity retained within these populations. The fact that the EV population is regionally restricted and its small census size of herd-book cows explain its high level of genomic inbreeding.

Improving Focal Photostimulation of Cortical Neurons with Pre-derived Wavefront Correction.

Recent progress in neuroscience to image and investigate brain function has been made possible by impressive developments in optogenetic and opto-molecular tools. Such research requires advances in optical techniques for the delivery of light through brain tissue with high spatial resolution. The tissue causes distortions to the wavefront of the incoming light which broadens the focus and consequently reduces the intensity and degrades the resolution. Such effects are detrimental in techniques requiring focal stimulation. Adaptive wavefront correction has been demonstrated to compensate for these distortions. However, iterative derivation of the corrective wavefront introduces time constraints that limit its applicability to probe living cells. Here, we demonstrate that we can pre-determine and generalize a small set of Zernike modes to correct for aberrations of the light propagating through specific brain regions. A priori identification of a corrective wavefront is a direct and fast technique that improves the quality of the focus without the need for iterative adaptive wavefront correction. We verify our technique by measuring the efficiency of two-photon photolysis of caged neurotransmitters along the dendrites of a whole-cell patched neuron. Our results show that encoding the selected Zernike modes on the excitation light can improve light propagation through brain slices of rats as observed by the neuron's evoked excitatory post-synaptic potential in response to localized focal uncaging at the spines of the neuron's dendrites.

Targeted pruning of a neuron's dendritic tree via femtosecond laser dendrotomy.

Neurons are classified according to action potential firing in response to current injection. While such firing patterns are shaped by the composition and distribution of ion channels, modelling studies suggest that the geometry of dendritic branches also influences temporal firing patterns. Verifying this link is crucial to understanding how neurons transform their inputs to output but has so far been technically challenging. Here, we investigate branching-dependent firing by pruning the dendritic tree of pyramidal neurons. We use a focused ultrafast laser to achieve highly localized and minimally invasive cutting of dendrites, thus keeping the rest of the dendritic tree intact and the neuron functional. We verify successful dendrotomy via two-photon uncaging of neurotransmitters before and after dendrotomy at sites around the cut region and via biocytin staining. Our results show that significantly altering the dendritic arborisation, such as by severing the apical trunk, enhances excitability in layer V cortical pyramidal neurons as predicted by simulations. This method may be applied to the analysis of specific relationships between dendritic structure and neuronal function. The capacity to dynamically manipulate dendritic topology or isolate inputs from various dendritic domains can provide a fresh perspective on the roles they play in shaping neuronal output.

Improved two-photon imaging of living neurons in brain tissue through temporal gating.

We optimize two-photon imaging of living neurons in brain tissue by temporally gating an incident laser to reduce the photon flux while optimizing the maximum fluorescence signal from the acquired images. Temporal gating produces a bunch of ~10 femtosecond pulses and the fluorescence signal is improved by increasing the bunch-pulse energy. Gating is achieved using an acousto-optic modulator with a variable gating frequency determined as integral multiples of the imaging sampling frequency. We hypothesize that reducing the photon flux minimizes the photo-damage to the cells. Our results, however, show that despite producing a high fluorescence signal, cell viability is compromised when the gating and sampling frequencies are equal (or effectively one bunch-pulse per pixel). We found an optimum gating frequency range that maintains the viability of the cells while preserving a pre-set fluorescence signal of the acquired two-photon images. The neurons are imaged while under whole-cell patch, and the cell viability is monitored as a change in the membrane's input resistance.

Low-cost photo-responsive nanocarriers by one-step functionalization of flame-made titania agglomerates with l-Lysine.

A novel versatile photo-responsive nanocarrier that is able to load and release several functional molecules is obtained by one-step conjugation of scalable flame-made titania agglomerates. Highly crystalline anatase nano-crystals are synthesized by scalable flame spray pyrolysis of organometallic precursor solutions. Nanocarriers are self-assembled by adsorption of lysine molecules on the photocatalytic nanoparticles' surface leading to a minimal flocculation and highly reactive amine terminations. Time-controlled photo-release of the ligand and end-loaded molecules is achieved by short exposure to UV light. The application of these flexible nanoplatforms to intracellular delivery is demonstrated by dye loading and two-photon microscopic in vitro imaging of their penetration in living neurons of Wistar rat brain tissue. These scalable photo-responsive nanocarriers are a flexible platform with potential for in vivo controlled release of amine-reactive dyes and amino-acid modified pro-drugs, as demonstrated by the successful loading and release of fluorescein isothiocyanate dye (FITC) and ketoprofen.

Evaluation of variant identification methods for whole genome sequencing data in dairy cattle.

BACKGROUND: Advances in human genomics have allowed unprecedented productivity in terms of algorithms, software, and literature available for translating raw next-generation sequence data into high-quality information. The challenges of variant identification in organisms with lower quality reference genomes are less well documented. We explored the consequences of commonly recommended preparatory steps and the effects of single and multi sample variant identification methods using four publicly available software applications (Platypus, HaplotypeCaller, Samtools and UnifiedGenotyper) on whole genome sequence data of 65 key ancestors of Swiss dairy cattle populations. Accuracy of calling next-generation sequence variants was assessed by comparison to the same loci from medium and high-density single nucleotide variant (SNV) arrays. RESULTS: The total number of SNVs identified varied by software and method, with single (multi) sample results ranging from 17.7 to 22.0 (16.9 to 22.0) million variants. Computing time varied considerably between software. Preparatory realignment of insertions and deletions and subsequent base quality score recalibration had only minor effects on the number and quality of SNVs identified by different software, but increased computing time considerably. Average concordance for single (multi) sample results with high-density chip data was 58.3% (87.0%) and average genotype concordance in correctly identified SNVs was 99.2% (99.2%) across software. The average quality of SNVs identified, measured as the ratio of transitions to transversions, was higher using single sample methods than multi sample methods. A consensus approach using results of different software generally provided the highest variant quality in terms of transition/transversion ratio. CONCLUSIONS: Our findings serve as a reference for variant identification pipeline development in non-human organisms and help assess the implication of preparatory steps in next-generation sequencing pipelines for organisms with incomplete reference genomes (pipeline code is included). Benchmarking this information should prove particularly useful in processing next-generation sequencing data for use in genome-wide association studies and genomic selection.

Four-dimensional multi-site photolysis of caged neurotransmitters.

Neurons receive thousands of synaptic inputs that are distributed in space and time. The systematic study of how neurons process these inputs requires a technique to stimulate multiple yet highly targeted points of interest along the neuron's dendritic tree. Three-dimensional multi-focal patterns produced via holographic projection combined with two-photon photolysis of caged compounds can provide for highly localized release of neurotransmitters within each diffraction-limited focus, and in this way emulate simultaneous synaptic inputs to the neuron. However, this technique so far cannot achieve time-dependent stimulation patterns due to fundamental limitations of the hologram-encoding device and other factors that affect the consistency of controlled synaptic stimulation. Here, we report an advanced technique that enables the design and application of arbitrary spatio-temporal photostimulation patterns that resemble physiological synaptic inputs. By combining holographic projection with a programmable high-speed light-switching array, we have overcome temporal limitations with holographic projection, allowing us to mimic distributed activation of synaptic inputs leading to action potential generation. Our experiments uniquely demonstrate multi-site two-photon glutamate uncaging in three dimensions with submillisecond temporal resolution. Implementing this approach opens up new prospects for studying neuronal synaptic integration in four dimensions.

Mathematical analysis and algorithms for efficiently and accurately implementing stochastic simulations of short-term synaptic depression and facilitation.

The release of neurotransmitter vesicles after arrival of a pre-synaptic action potential (AP) at cortical synapses is known to be a stochastic process, as is the availability of vesicles for release. These processes are known to also depend on the recent history of AP arrivals, and this can be described in terms of time-varying probabilities of vesicle release. Mathematical models of such synaptic dynamics frequently are based only on the mean number of vesicles released by each pre-synaptic AP, since if it is assumed there are sufficiently many vesicle sites, then variance is small. However, it has been shown recently that variance across sites can be significant for neuron and network dynamics, and this suggests the potential importance of studying short-term plasticity using simulations that do generate trial-to-trial variability. Therefore, in this paper we study several well-known conceptual models for stochastic availability and release. We state explicitly the random variables that these models describe and propose efficient algorithms for accurately implementing stochastic simulations of these random variables in software or hardware. Our results are complemented by mathematical analysis and statement of pseudo-code algorithms.

Interaction of short-term depression and firing dynamics in shaping single neuron encoding.

We investigated how the two properties short-term synaptic depression of afferent input and postsynaptic firing dynamics combine to determine the operating mode of a neuron. While several computational roles have been ascribed to either, their interaction has not been studied. We considered two types of short-term synaptic dynamics (release-dependent and release-independent depression) and two classes of firing dynamics (regular firing and firing with spike-frequency adaptation). The input-output transformation of the four possible combinations of pre- and post-synaptic dynamics was characterized. Adapting neurons receiving input from release-dependent synapses functioned largely as coincidence detectors. The other three configurations showed properties consistent with integrators, each with distinct features. These results suggest that the operating mode of a neuron is determined by both the pre- and post-synaptic dynamics and that studying them together is necessary to understand emergent properties and their implications for neuronal coding.

Quantifying impacts of short-term plasticity on neuronal information transfer.

Short-term changes in efficacy have been postulated to enhance the ability of synapses to transmit information between neurons, and within neuronal networks. Even at the level of connections between single neurons, direct confirmation of this simple conjecture has proven elusive. By combining paired-cell recordings, realistic synaptic modeling, and information theory, we provide evidence that short-term plasticity can not only improve, but also reduce information transfer between neurons. We focus on a concrete example in rat neocortex, but our results may generalize to other systems. When information is contained in the timings of individual spikes, we find that facilitation, depression, and recovery affect information transmission in proportion to their impacts upon the probability of neurotransmitter release. When information is instead conveyed by mean spike rate only, the influences of short-term plasticity critically depend on the range of spike frequencies that the target network can distinguish (its effective dynamic range). Our results suggest that to efficiently transmit information, the brain must match synaptic type, coding strategy, and network connectivity during development and behavior.

Using whole-genome sequence data to predict quantitative trait phenotypes in Drosophila melanogaster.

Predicting organismal phenotypes from genotype data is important for plant and animal breeding, medicine, and evolutionary biology. Genomic-based phenotype prediction has been applied for single-nucleotide polymorphism (SNP) genotyping platforms, but not using complete genome sequences. Here, we report genomic prediction for starvation stress resistance and startle response in Drosophila melanogaster, using ∼2.5 million SNPs determined by sequencing the Drosophila Genetic Reference Panel population of inbred lines. We constructed a genomic relationship matrix from the SNP data and used it in a genomic best linear unbiased prediction (GBLUP) model. We assessed predictive ability as the correlation between predicted genetic values and observed phenotypes by cross-validation, and found a predictive ability of 0.239±0.008 (0.230±0.012) for starvation resistance (startle response). The predictive ability of BayesB, a Bayesian method with internal SNP selection, was not greater than GBLUP. Selection of the 5% SNPs with either the highest absolute effect or variance explained did not improve predictive ability. Predictive ability decreased only when fewer than 150,000 SNPs were used to construct the genomic relationship matrix. We hypothesize that predictive power in this population stems from the SNP-based modeling of the subtle relationship structure caused by long-range linkage disequilibrium and not from population structure or SNPs in linkage disequilibrium with causal variants. We discuss the implications of these results for genomic prediction in other organisms.