H3K9me2/3 Binding of the MBT Domain Protein LIN-61 Is Essential for Caenorhabditis elegans Vulva Development

MBT domain proteins are involved in developmental processes and tumorigenesis. In vitro binding and mutagenesis studies have shown that individual MBT domains within clustered MBT repeat regions bind mono- and dimethylated histone lysine residues with little to no sequence specificity but discriminate against the tri- and unmethylated states. However, the exact function of promiscuous histone methyl-lysine binding in the biology of MBT domain proteins has not been elucidated. Here, we show that the Caenorhabditis elegans four MBT domain protein LIN-61, in contrast to other MBT repeat factors, specifically interacts with histone H3 when methylated on lysine 9, displaying a strong preference for di- and trimethylated states (H3K9me2/3). Although the fourth MBT repeat is implicated in this interaction, H3K9me2/3 binding minimally requires MBT repeats two to four. Further, mutagenesis of residues conserved with other methyl-lysine binding MBT regions in the fourth MBT repeat does not abolish interaction, implicating a distinct binding mode. In vivo, H3K9me2/3 interaction of LIN-61 is required for C. elegans vulva development within the synMuvB pathway. Mutant LIN-61 proteins deficient in H3K9me2/3 binding fail to rescue lin-61 synMuvB function. Also, previously identified point mutant synMuvB alleles are deficient in H3K9me2/3 interaction although these target residues that are outside of the fourth MBT repeat. Interestingly, lin-61 genetically interacts with two other synMuvB genes, hpl-2, an HP1 homologous H3K9me2/3 binding factor, and met-2, a SETDB1 homologous H3K9 methyl transferase (H3K9MT), in determining C. elegans vulva development and fertility. Besides identifying the first sequence specific and di-/trimethylation binding MBT domain protein, our studies imply complex multi-domain regulation of ligand interaction of MBT domains. Our results also introduce a mechanistic link between LIN-61 function and biology, and they establish interplay of the H3K9me2/3 binding proteins, LIN-61 and HPL-2, as well as the H3K9MT MET-2 in distinct developmental pathways

Econometric Forecasting

Several principles are useful for econometric forecasters: keep the model simple, use all the data you can get, and use theory (not the data) as a guide to selecting causal variables. But theory gives little guidance on dynamics, that is, on which lagged values of the selected variables to use. Early econometric models failed in comparison with extrapolative methods because they paid too little attention to dynamic structure. In a fairly simple way, the vector autoregression (VAR) approach that first appeared in the 1980s resolved the problem by shifting emphasis towards dynamics and away from collecting many causal variables. The VAR approach also resolves the question of how to make long-term forecasts where the causal variables themselves must be forecast. When the analyst does not need to forecast causal variables or can use other sources, he or she can use a single equation with the same dynamic structure. Ordinary least squares is a perfectly adequate estimation method. Evidence supports estimating the initial equation in levels, whether the variables are stationary or not. We recommend a general-to-specific model-building strategy: start with a large number of lags in the initial estimation, although simplifying by reducing the number of lags pays off. Evidence on the value of further simplification is mixed. If cointegration among variables, then error-correction models (ECMs) will do worse than equations in levels. But ECMs are only sometimes an improvement eve