No abstract

A major line of evidence that supports the hypothesis of dopamine overactivity in schizophrenia is the psychomimetic potential of agents such as amphetamine that stimulate dopamine outf low. A novel brain imaging method provides an indirect measure of in vivo synaptic dopamine concentration by quantifying the change in dopamine receptor radiotracer binding produced by agents that alter dopamine release but do not themselves bind to dopamine receptors. The purpose of this investigation is (i) to determine the sensitivity (i.e., amount of dopamine ref lected in radiotracer binding changes) of this method by examining the relationship between amphetamine-induced changes in simultaneously derived striatal extracellular dopamine levels with in vivo microdialysis and striatal binding levels with the dopamine D 2 ͞D 3 positron-emission tomography radioligand [ 11 C]raclopride in nonhuman primates, and (ii) to test the hypothesis of elevated amphetamine-induced synaptic dopamine levels in schizophrenia. In the nonhuman primate study (n ‫؍‬ 4), doubling the amphetamine dose produced a doubling in [ 11 C]raclopride specific binding reductions. In addition, the ratio of percent mean dopamine increase to percent mean striatal binding reduction for amphetamine (0.2 mg͞kg) was 44:1, demonstrating that relatively small binding changes ref lect large changes in dopamine outf low. In the clinical study, patients with schizophrenia (n ‫؍‬ 11) compared with healthy volunteers (n ‫؍‬ 12) had significantly greater amphetamine-related reductions in [ 11 C]raclopride specific binding (mean ؎ SEM): ؊22.3% (؎2.7) vs. ؊15.5% (؎1.8), P ‫؍‬ 0.04, respectively. Inferences from the preclinical study suggest that the patients' elevation in synaptic dopamine concentrations was substantially greater than controls. These data provide direct evidence for the hypothesis of elevated amphetamineinduced synaptic dopamine concentrations in schizophrenia.

Determining the genome sequence of an organism is challenging, yet fundamental to understanding its biology. Over the past decade, thousands of human genomes have been sequenced, contributing deeply to biomedical research. In the vast majority of cases, these have been analyzed by aligning sequence reads to a single reference genome, biasing the resulting analyses, and in general, failing to capture sequences novel to a given genome. Some de novo assemblies have been constructed free of reference bias, but nearly all were constructed by merging homologous loci into single "consensus" sequences, generally absent from nature. These assemblies do not correctly represent the diploid biology of an individual. In exactly two cases, true diploid de novo assemblies have been made, at great expense. One was generated using Sanger sequencing, and one using thousands of clone pools. Here, we demonstrate a straightforward and low-cost method for creating true diploid de novo assemblies. We make a single library from ∼1 ng of high molecular weight DNA, using the 10x Genomics microfluidic platform to partition the genome. We applied this technique to seven human samples, generating low-cost HiSeq X data, then assembled these using a new "pushbutton" algorithm, Supernova. Each computation took 2 d on a single server. Each yielded contigs longer than 100 kb, phase blocks longer than 2.5 Mb, and scaffolds longer than 15 Mb. Our method provides a scalable capability for determining the actual diploid genome sequence in a sample, opening the door to new approaches in genomic biology and medicine.

Determining the genome sequence of an organism is challenging, yet fundamental to understanding its biology. Over the past decade, thousands of human genomes have been sequenced, contributing deeply to biomedical research. In the vast majority of cases, these have been analyzed by aligning sequence reads to a single reference genome, biasing the resulting analyses and, in general, failing to capture sequences novel to a given genome.Some de novo assemblies have been constructed, free of reference bias, but nearly all were constructed by merging homologous loci into single ‘consensus’ sequences, generally absent from nature. These assemblies do not correctly represent the diploid biology of an individual. In exactly two cases, true diploid de novo assemblies have been made, at great expense. One was generated using Sanger sequencing and one using thousands of clone pools.Here we demonstrate a straightforward and low-cost method for creating true diploid de novo assemblies. We make a single library from ~1 ng of high molecular weight DNA, using the 10x Genomics microfluidic platform to partition the genome. We applied this technique to seven human samples, generating low-cost HiSeq X data, then assembled these using a new ‘pushbutton’ algorithm, Supernova. Each computation took two days on a single server. Each yielded contigs longer than 100 kb, phase blocks longer than 2.5 Mb, and scaffolds longer than 15 Mb. Our method provides a scalable capability for determining the actual diploid genome sequence in a sample, opening the door to new approaches in genomic biology and medicine.