Genes on different chromosomes can be spatially associated in the nucleus in several transcriptional and regulatory situations; however, the functional significance of such associations remains unclear. Using human erythropoiesis as a model, we show that five cotranscribed genes, which are found on four different chromosomes, associate with each other at significant but variable frequencies. Those genes most frequently in association lie in decondensed stretches of chromatin. By replacing the mouse α-globin gene cluster in situ with its human counterpart, we demonstrate a direct effect of the regional chromatin environment on the frequency of association, whereas nascent transcription from the human α-globin gene appears unaffected. We see no evidence that cotranscribed erythroid genes associate at shared transcription foci, but we do see stochastic clustering of active genes around common nuclear SC35-enriched speckles (hence the apparent nonrandom association between genes). Thus, association between active genes may result from their location on decondensed chromatin that enables clustering around common nuclear speckles.

We have devised a strategy (called recombinase-mediated genomic replacement, RMGR) to allow the replacement of large segments (>100 kb) of the mouse genome with the equivalent human syntenic region. The technique involves modifying a mouse ES cell chromosome and a human BAC by inserting heterotypic lox sites to flank the proposed exchange interval and then using Cre recombinase to achieve segmental exchange. We have demonstrated the feasibility of this approach by replacing the mouse alpha globin regulatory domain with the human syntenic region and generating homozygous mice that produce only human alpha globin chains. Furthermore, modified ES cells can be used iteratively for functional studies, and here, as an example, we have used RMGR to produce an accurate mouse model of human alpha thalassemia. RMGR has general applicability and will overcome limitations inherent in current transgenic technology when studying the expression of human genes and modeling human genetic diseases.

qPET methodology provides semi-automatic quantification for interim FDG-PET response in lymphoma extending ordinal Deauville scoring to a continuous scale. Deauville categories correspond to certain qPET cut values. Thresholds between normal and abnormal response can be derived from the qPET-distribution without need for follow-up data. In our patients, qPET < 1.3 excludes abnormal response with high sensitivity.

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