Biology subjects

Kleckner, N.

Publications and source records attributed to Kleckner, N..

4 recordsLinked to original sources

bioRxiv2024

Rapid Homolog Juxtaposition During Meiotic Chromosome Pairing

A central basic feature of meiosis is pairing of homologous maternal and paternal chromosomes ("homologs") intimately along their lengths. Recognition between homologs and their juxtaposition in space are mediated by axis-associated DNA recombination complexes. Additional effects ensure that pairing occurs without ultimately giving entanglements among unrelated chromosomes. Here we examine the process of homolog juxtaposition in real time by 4D fluorescence imaging of tagged chromosomal loci at high spatio-temporal resolution in budding yeast. We discover that corresponding loci start coming together from a quite large distance ([~]1.8 {micro}m) and progress to completion of pairing in a very short time, usually less than six minutes (thus, "rapid homolog juxtaposition" or "RHJ"). Juxtaposition initiates by motion-mediated extension of a nascent interhomolog DNA linkage, raising the possibility of a tension-mediated trigger. In a first transition, homolog loci move rapidly together (in [~]30 sec, at speeds of up to [~]60 nm/sec) into a discrete intermediate state corresponding to canonical [~]400 nm axis distance coalignment. Then, after a short pause, crossover/noncrossover differentiation (crossover interference) mediates a second short, rapid transition that brings homologs even closer together. If synaptonemal complex (SC) component Zip1 is present, this transition concomitantly gives final close pairing by axis juxtaposition at [~]100 nm, the "SC distance". We also find that: (i) RHJ occurs after chromosomes acquire their prophase chromosome organization; (ii) is nearly synchronously over thirds (or more) of chromosome lengths; but (iii) is asynchronous throughout the genome. Furthermore, cytoskeleton-mediated movement is important for the timing and distance of RHJ onset and also for ensuring normal progression. Potential implications for local and global aspects of pairing are discussed.

molecular biology↗

bioRxiv2019

A general quantitative relation linking bacterial cell growth and the cell cycle

The foundation of bacterial cell cycle studies has long resided in two interconnected dogmas between biomass growth, DNA replication, and cell division during exponential growth: the SMK growth law that relates cell mass (a measure of cell size) to growth rate1, and Donachies hypothesis of a growth-rate-independent initiation mass2. These dogmas have spurred many efforts to understand their molecular bases and physiological consequences3-12. Most of these studies focused on fast-growing cells, with doubling times shorter than 60 min. Here, we systematically studied the cell cycle of E. coli for a broad range of doubling times (24 min to over 10 hr), with particular attention on steady-state growth. Surprisingly, we observed that neither dogma held across the range of growth rates examined. In their stead, a new linear relation unifying the slow- and fast-growth regimes was revealed between the cell mass and the number of cell divisions it takes to replicate and segregate a newly initiated pair of replication origins. This and other findings in this study suggest a single-cell division model, which not only reproduces the bulk relations observed but also recapitulates the adder phenomenon established recently for stochastically dividing cells13-15. These results allowed us to develop quantitative insight into the bacterial cell cycle, providing a firm new foundation for the study of bacterial growth physiology.

microbiology↗

bioRxiv2017

DNA sequence homology induces cytosine-to-thymine mutation by a heterochromatin-related pathway

In the genomes of many eukaryotes, including mammals, highly repetitive DNA is normally associated with histone H3 lysine-9 di-/trimethylation (H3K9me2/3) and C5-cytosine methylation (5mC) in the context of heterochromatin. In the fungus Neurospora crassa, H3K9me3 and 5mC are catalyzed, respectively, by a conserved SUV39 histone methylase DIM-5 and a DNMT1-like cytosine methylase DIM-2. Here we show that DIM-2 can also mediate cytosine-to-thymine mutation of repetitive DNA during the pre-meiotic process known as Repeat-Induced Point mutation (RIP) in N. crassa. We further show that DIM-2-dependent RIP requires DIM-5, HP1, and other heterochromatin factors, implying the involvement of a repeat-induced heterochromatin-related process. Our previous findings suggest that the mechanism of homologous repeat recognition for RIP involves direct pairwise interactions between co-aligned double-stranded (ds) DNA segments. Our current findings therefore raise the possibility that such pairing interactions may occur not only in pre-meiotic but also in vegetative cells, where they may direct heterochromatin assembly on repetitive DNA. In accord with this possibility, we find that, in vegetative cells of N. crassa, our model repeat array comprising only four 674-bp sequence copies can trigger a low level of DIM-5-dependent 5meC. We thus propose that homologous dsDNA/dsDNA interactions between a small number of repeat copies can nucleate a transient state of heterochromatin and that, on longer repeat arrays, such interactions lead to the formation of stable heterochromatin. Since the number of possible pairwise dsDNA/dsDNA interactions will scale non-linearly with the number of repeats, this mechanism provides an attractive way of creating the extended domains of constitutive heterochromatin found in pericentromeric and subtelomeric regions.

molecular biology↗

bioRxiv2016

Quantitative Modeling and Automated Analysis of Meiotic Recombination

Many morphological features, in both physical and biological systems, exhibit spatial patterns that are specifically characterized by a tendency to occur with even spacing (in one, two or three dimensions). The positions of crossover (CO) recombination events along meiotic chromosomes provides an interesting biological example of such an effect (1-3). In general, mechanisms that explain such patterns may (a) be mechanically-based, (b) occur by a reaction-diffusion mechanism in which macroscopic mechanical effects are irrelevant, or (c) involve a combination of both types of effects. We have proposed that meiotic CO patterns arise by a mechanical mechanism, have developed mathematical expressions for such a process based on a particular physical system with analogous properties (the so-called \"beam-film model\"), and have shown that the beam-film model can very accurately explain experimental CO patterns as a function of the values of specific defined parameters (4-7). Importantly, the mathematical expressions of the beam-film model can apply quite generally to any mechanism, whether it involves mechanical components or not, as long as its logic and component features correspond to those of the beam-film system (3; below). Furthermore, via its various parameters, the beam-film model discretizes the patterning process into specific components. Thus, the model can be used to explore the theoretically predicted effects of various types of changes in the patterning process. Such predictions can expand detailed understanding of the bases for various biological effects (e.g. 2, 5). We present here a new MATLAB program that implements the mathematical expressions of the beam-film model with increased robustness and accessibility as compared to programs presented previously. As in previous versions, the presented program permits both: (i) simulation of predicted CO positions along chromosomes of a test population; and (ii) easy analysis of CO positions, both for experimental data sets and for data sets resulting from simulations. The goal of the current presentation is to make these approaches more readily accessible to a wider audience of researchers. Also, the program is easily modified, and we encourage interested users to make changes to suit their specific needs. A link to the program is available on the Kleckner laboratory web site: http://projects.iq.harvard.edu/kleckner_lab.

genetics↗