Integration of multiple instructive cues by neural crest stem cells reveals cell-intrinsic biases in relative growth factor responsiveness

Growth factors can influence lineage determination of neural crest stem cells (NCSCs) in an instructive manner, in vitro. Because NCSCs are likely exposed to multiple signals in vivo, these findings raise the question of how stem cells would integrate such combined influences. Bone morphogenetic protein 2 (BMP2) promotes neuronal differentiation and glial growth factor 2 (GGF2) promotes glial differentiation; if NCSCs are exposed to saturating concentrations of both factors, BMP2 appears dominant. By contrast, if the cells are exposed to saturating concentrations of both BMP2 and transforming growth factor β1 (which promotes smooth muscle differentiation), the two factors appear codominant. Sequential addition experiments indicate that NCSCs require 48–96 hrs in GGF2 before they commit to a glial fate, whereas the cells commit to a smooth muscle fate within 24 hr in transforming growth factor β1. The delayed response to GGF2 does not reflect a lack of functional receptors; however, because the growth factor induces rapid mitogen-activated protein kinase phosphorylation in naive cells. Furthermore, GGF2 can attenuate induction of the neurogenic transcription factor mammalian achaete-scute homolog 1, by low doses of BMP2. This short-term antineurogenic influence of GGF2 is not sufficient for glial lineage commitment, however. These data imply that NCSCs exhibit cell-intrinsic biases in the timing and relative dosage sensitivity of their responses to instructive factors that influence the outcome of lineage decisions in the presence of multiple factors. The relative delay in glial lineage commitment, moreover, apparently reflects successive short-term and longer-term actions of GGF2. Such a delay may help to explain why glia normally differentiate after neurons, in vivo.

Compositional differences within and between eukaryotic genomes

Eukaryotic genome similarity relationships are inferred using sequence information derived from large aggregates of genomic sequences. Comparisons within and between species sample sequences are based on the profile of dinucleotide relative abundance values (The profile is ρ*XY = f*XY/f*Xf*Y for all XY, where f*X denotes the frequency of the nucleotide X and f*XY denotes the frequency of the dinucleotide XY, both computed from the sequence concatenated with its inverted complement). Previous studies with respect to prokaryotes and this study document that profiles of different DNA sequence samples (sample size ≥50 kb) from the same organism are generally much more similar to each other than they are to profiles from other organisms, and that closely related organisms generally have more similar profiles than do distantly related organisms. On this basis we refer to the collection {ρ*XY} as the genome signature. This paper identifies ρ*XY extremes and compares genome signature differences for a diverse range of eukaryotic species. Interpretations on the mechanisms maintaining these profile differences center on genome-wide replication, repair, DNA structures, and context-dependent mutational biases. It is also observed that mitochondrial genome signature differences between species parallel the corresponding nuclear genome signature differences despite large differences between corresponding mitochondrial and nuclear signatures. The genome signature differences also have implications for contrasts between rodents and other mammals, and between monocot and dicot plants, as well as providing evidence for similarities among fungi and the diversity of protists.

The atypical codon usage of the plant psbA gene may be the remnant of an ancestral bias

The psbA gene of the chloroplast genome has a codon usage that is unusual for plant chloroplast genes. In the present study the evolutionary status of this codon usage is tested by reconstructing putative ancestral psbA sequences to determine the pattern of change in codon bias during angiosperm divergence. It is shown that the codon biases of the ancestral genes are much stronger than all extant flowering plant psbA genes. This is related to previous work that demonstrated a significant increase in synonymous substitution in psbA relative to other chloroplast genes. It is suggested, based on the two lines of evidence, that the codon bias of this gene currently is not being maintained by selection. Rather, the atypical codon bias simply may be a remnant of an ancestral codon bias that now is being degraded by the mutation bias of the chloroplast genome, in other words, that the psbA gene is not at equilibrium. A model for the evolution of selective pressure on the codon usage of plant chloroplast genes is discussed.

A physical basis for protein secondary structure

A physical theory of protein secondary structure is proposed and tested by performing exceedingly simple Monte Carlo simulations. In essence, secondary structure propensities are predominantly a consequence of two competing local effects, one favoring hydrogen bond formation in helices and turns, the other opposing the attendant reduction in sidechain conformational entropy on helix and turn formation. These sequence specific biases are densely dispersed throughout the unfolded polypeptide chain, where they serve to preorganize the folding process and largely, but imperfectly, anticipate the native secondary structure.

LC2, the Chlamydomonas Homologue of the t Complex-encoded Protein Tctex2, Is Essential for Outer Dynein Arm Assembly

Tctex2 is thought to be one of the distorter genes of the mouse t haplotype. This complex greatly biases the segregation of the chromosome that carries it such that in heterozygous +/t males, the t haplotype is transmitted to >95% of the offspring, a phenomenon known as transmission ratio distortion. The LC2 outer dynein arm light chain of Chlamydomonas reinhardtii is a homologue of the mouse protein Tctex2. We have identified Chlamydomonas insertional mutants with deletions in the gene encoding LC2 and demonstrate that the LC2 gene is the same as the ODA12 gene, the product of which had not been identified previously. Complete deletion of the LC2/ODA12 gene causes loss of all outer arms and a slow jerky swimming phenotype. Transformation of the deletion mutant with the cloned LC2/ODA12 gene restores the outer arms and rescues the motility phenotype. Therefore, LC2 is required for outer arm assembly. The fact that LC2 is an essential subunit of flagellar outer dynein arms allows us to propose a detailed mechanism whereby transmission ratio distortion is explained by the differential binding of mutant (t haplotype encoded) and wild-type dyneins to the axonemal microtubules of t-bearing or wild-type sperm, with resulting differences in their motility.

A preference for own-subspecies' song guides vocal learning in a song bird

In many song birds, males develop their songs as adults by imitating the songs of one or more tutors, memorized previously during a sensitive phase early in life. Previous work using two assays, the production of imitations by adult males and playback-induced calling by young birds during the sensitive phase for memorization, has shown that song birds can discriminate between their own and other species' songs. Herein I use both assays to show that male mountain white-crowned sparrows, Zonotrichia leucophrys oriantha, must learn to sing but have a genetic predisposition to memorize and learn the songs of their own subspecies. Playback tests to young naive birds before they even begin to sing reveal that birds give begging calls more in response to oriantha song than to songs of another species. After 10 days of tutoring with songs of either their own or another subspecies, birds continue to give stronger call responses to songs of their own subspecies, irrespective of whether they were tutored with them, and are more discriminating in distinguishing between different dialects of their own subspecies. The memory processes that facilitate recognition and discrimination of own-subspecies' song may also mediate the preferential imitation of song of a bird's own subspecies. Such perceptual biases could constrain the direction and rate of cultural evolution of learned songs.

Comparison of intron-containing and intron-lacking human genes elucidates putative exonic splicing enhancers

Of the rules used by the splicing machinery to precisely determine intron–exon boundaries only a fraction is known. Recent evidence suggests that specific short sequences within exons help in defining these boundaries. Such sequences are known as exonic splicing enhancers (ESE). A possible bioinformatical approach to studying ESE sequences is to compare genes that harbor introns with genes that do not. For this purpose two non-redundant samples of 719 intron-containing and 63 intron-lacking human genes were created. We performed a statistical analysis on these datasets of intron-containing and intron-lacking human coding sequences and found a statistically significant difference (P = 0.01) between these samples in terms of 5–6mer oligonucleotide distributions. The difference is not created by a few strong signals present in the majority of exons, but rather by the accumulation of multiple weak signals through small variations in codon frequencies, codon biases and context-dependent codon biases between the samples. A list of putative novel human splicing regulation sequences has been elucidated by our analysis.

Estimating risks in declining populations with poor data

Census data on endangered species are often sparse, error-ridden, and confined to only a segment of the population. Estimating trends and extinction risks using this type of data presents numerous difficulties. In particular, the estimate of the variation in year-to-year transitions in population size (the “process error” caused by stochasticity in survivorship and fecundities) is confounded by the addition of high sampling error variation. In addition, the year-to-year variability in the segment of the population that is sampled may be quite different from the population variability that one is trying to estimate. The combined effect of severe sampling error and age- or stage-specific counts leads to severe biases in estimates of population-level parameters. I present an estimation method that circumvents the problem of age- or stage-specific counts and is markedly robust to severe sampling error. This method allows the estimation of environmental variation and population trends for extinction-risk analyses using corrupted census counts—a common type of data for endangered species that has hitherto been relatively unusable for these analyses.