In vitro development of day-2 equine embryos co-cultured with oviductal explants or trophoblastic vesicles

This study compared the in vitro development of Day-2 equine embryos co-cultured with either trophoblastic vesicles or oviductal explants. Embryos were collected surgically from the oviducts of pony mares 2 d after ovulation and assessed for stage of development. Culture medium was Ham's F12 and Dulbecco's Modified Eagle's Medium (50:50 v/v) in a humidified atmosphere of 5% CO(2) in air at 38.5 degrees C with either trophoblastic vesicles or oviductal explants. The quality score of embryos was assessed daily. After 4 d in culture, embryos were stained (Hoechst 33342) and evaluated with epifluorescence to determine the number of nuclei present. Six of seven embryos co-cultured with oviductal exmplants developed to the morula/blastocyst stage, while four of seven embryos co-cultured with trophoblastic vesicles developed to the morula stage. More (P = 0.1) embryos co-cultured with oviductal explants reached the blastocyst stage than embryos co-cultured with trophoblastic vesicles (3 7 vs 0 7 , respectively). The number of cells was higher (P = 0.1) for embryos co-cultured with oviductal explants than for embryos co-cultured with trophoblastic vesicles (162.6 +/- 32 vs 87.3 +/- 28, respectively). The number of cells for embryos co-cultured with either oviductal explants or trophoblastic vesicles appeared to be lower than for embryos matured in vivo that were recovered from the uterus at Day 6 (378, 399, >1000). The co-culture of early equine embryos in a completely defined medium with either trophoblastic vesicles or oviductal explants can support development to at least the morula stage. The co-culture of embryos with oviductal explants resulted in superior development of four-to eight-cell embryos, as indicated by the proportion that reached the blastocyst stage and by the number of cells.     

Isolation and characterization of peanut spherosomes

Spherosomes of cotyledons of germinating peanuts (Arachis hypogea L.) were examined by electron microscopy and found to be particles about 1.0 to 2.0 μ in diameter bounded by a limiting membrane. Isolated spherosomes appear similar to spherosomes in situ. The isolated spherosomes are composed of 98.1% total lipids, 0.77% phospholipid and 1.27% protein by dry weight. The amounts of protein and phospholipid associated with the isolated spherosomes are sufficient to account for limiting membranes. Spherosomes amply account for the lipid in a peanut cotyledon. The activity of lipase and fatty acyl-Coenzyme A synthetase is not associated with the isolated spherosomes. This suggests that peanut spherosomes are principal sites of lipid storage but not of lipid degradation.     

Weights for data related by a tree

How can one characterize a set of data collected from different biological species, or indeed any set of data related by an evolutionary tree? The structure imposed by the tree implies that the data are not independent, and for most applications this should be taken into account. We describe strategies for weighting the data that circumvent some of the problems of dependency.     

Gap costs for multiple sequence alignment

Standard methods for aligning pairs of biological sequences charge for the most common mutations, which are substitutions, deletions and insertions. Because a single mutation may insert or delete several nucleotides, gap costs that are not directly proportional to gap length are usually the most effective. How to extend such gap costs to alignments of three or more sequences is not immediately obvious, and a variety of approaches have been taken. This paper argues that, since gap and substitution costs together specify optimal alignments, they should be defined using a common rationale. Specifically, a new definition of gap costs for multiple alignments is proposed and compared with previous ones. Since the new definition links a multiple alignment's cost to that of its pairwise projections, it allows knowledge gained about two-sequence alignments to bear on the multiple alignment problem. Also, such linkage is a key element of recent algorithms that have rendered practical the simultaneous alignment of as many as six sequences.     

A protein alignment scoring system sensitive at all evolutionary distances

Summary Protein sequence alignments generally are constructed with the aid of a substitution matrix that specifies a score for aligning each pair of amino acids. Assuming a simple random protein model, it can be shown that any such matrix, when used for evaluating variable-length local alignments, is implicitly a log-odds matrix, with a specific probability distribution for amino acid pairs to which it is uniquely tailored. Given a model of protein evolution from which such distributions may be derived, a substitution matrix adapted to detecting relationships at any chosen evolutionary distance can be constructed. Because in a database search it generally is not known a priori what evolutionary distances will characterize the similarities found, it is necessary to employ an appropriate range of matrices in order not to overlook potential homologies. This paper formalizes this concept by defining a scoring system that is sensitive at all detectable evolutionary distances. The statistical behavior of this scoring system is analyzed, and it is shown that for a typical protein database search, estimating the originally unknown evolutionary distance appropriate to each alignment costs slightly over two bits of information, or somewhat less than a factor of five in statistical significance. A much greater cost may be incurred, however, if only a single substitution matrix, corresponding to the wrong evolutionary distance, is employed.     

Amino acid substitution matrices from an information theoretic perspective

Protein sequence alignments have become an important tool for molecular biologists. Local alignments are frequently constructed with the aid of a "substitution score matrix" that specifies a score for aligning each pair of amino acid residues. Over the years, many different substitution matrices have been proposed, based on a wide variety of rationales. Statistical results, however, demonstrate that any such matrix is implicitly a "log-odds" matrix, with a specific target distribution for aligned pairs of amino acid residues. In the light of information theory, it is possible to express the scores of a substitution matrix in bits and to see that different matrices are better adapted to different purposes. The most widely used matrix for protein sequence comparison has been the PAM-250 matrix. It is argued that for database searches the PAM-120 matrix generally is more appropriate, while for comparing two specific proteins with suspected homology the PAM-200 matrix is indicated. Examples discussed include the lipocalins, human alpha 1 B-glycoprotein, the cystic fibrosis transmembrane conductance regulator and the globins.     

The Construction and Use of Log-Odds Substitution Scores for Multiple Sequence Alignment

Most pairwise and multiple sequence alignment programs seek alignments with optimal scores. Central to defining such scores is selecting a set of substitution scores for aligned amino acids or nucleotides. For local pairwise alignment, substitution scores are implicitly of log-odds form. We now extend the log-odds formalism to multiple alignments, using Bayesian methods to construct “BILD” (“Bayesian Integral Log-odds”) substitution scores from prior distributions describing columns of related letters. This approach has been used previously only to define scores for aligning individual sequences to sequence profiles, but it has much broader applicability. We describe how to calculate BILD scores efficiently, and illustrate their uses in Gibbs sampling optimization procedures, gapped alignment, and the construction of hidden Markov model profiles. BILD scores enable automated selection of optimal motif and domain model widths, and can inform the decision of whether to include a sequence in a multiple alignment, and the selection of insertion and deletion locations. Other applications include the classification of related sequences into subfamilies, and the definition of profile-profile alignment scores. Although a fully realized multiple alignment program must rely upon more than substitution scores, many existing multiple alignment programs can be modified to employ BILD scores. We illustrate how simple BILD score based strategies can enhance the recognition of DNA binding domains, including the Api-AP2 domain in Toxoplasma gondii and Plasmodium falciparum.