Identification of residue inversions in large phylogenies of duplicated proteins

Connecting protein sequence to function is becoming increasingly relevant since high-throughput sequencing studies accumulate large amounts of genomic data. Protein database annotation helps to bridge this gap; however, it is fundamental to understand the mechanisms underlying functional inheritance and divergence. If the homology relationship between proteins is known, can we determine whether the function diverged? In this work, we analyze different possibilities of protein sequence evolution after gene duplication and identify "residue inversions", i.e., sites where the relationship between the ancestry and the functional signal is decoupled. Residues in these sites play a role in functional divergence and could indicate a shift in protein function. We develop a method to recognize residue inversions in a phylogeny and test it on real and simulated datasets. In a dataset built from the Epidermal Growth Factor Receptor (EGFR) sequences found in 88 fish species, we identify 19 positions that went through inversion after gene duplication, mostly located at the ligand-binding extracellular domain.

FoldRec-C2C: protein fold recognition by combining cluster-to-cluster model and protein similarity network

As a key for studying the protein structures, protein fold recognition is playing an important role in predicting the protein structures associated with COVID-19 and other important structures. However, the existing computational predictors only focus on the protein pairwise similarity or the similarity between two groups of proteins from 2-folds. However, the homology relationship among proteins is in a hierarchical structure. The global protein similarity network will contribute to the performance improvement. In this study, we proposed a predictor called FoldRec-C2C to globally incorporate the interactions among proteins into the prediction. For the FoldRec-C2C predictor, protein fold recognition problem is treated as an information retrieval task in nature language processing. The initial ranking results were generated by a surprised ranking algorithm Learning to Rank, and then three re-ranking algorithms were performed on the ranking lists to adjust the results globally based on the protein similarity network, including seq-to-seq model, seq-to-cluster model and cluster-to-cluster model (C2C). When tested on a widely used and rigorous benchmark dataset LINDAHL dataset, FoldRec-C2C outperforms other 34 state-of-the-art methods in this field. The source code and data of FoldRec-C2C can be downloaded from http://bliulab.net/FoldRec-C2C/download.

A Logical Model of Homology for Comparative Biology

There is a growing body of research on the evolution of anatomy in a wide variety of organisms. Discoveries in this field could be greatly accelerated by computational methods and resources that enable these findings to be compared across different studies and different organisms and linked with the genes responsible for anatomical modifications. Homology is a key concept in comparative anatomy; two important types are historical homology (the similarity of organisms due to common ancestry) and serial homology (the similarity of repeated structures within an organism). We explored how to most effectively represent historical and serial homology across anatomical structures to facilitate computational reasoning. We assembled a collection of homology assertions from the literature with a set of taxon phenotypes for the skeletal elements of vertebrate fins and limbs from the Phenoscape Knowledgebase. Using seven competency questions, we evaluated the reasoning ramifications of two logical models: the Reciprocal Existential Axioms (REA) homology model and the Ancestral Value Axioms (AVA) homology model. The AVA model returned all user-expected results in addition to the search term and any of its subclasses. The AVA model also returns any superclass of the query term in which a homology relationship has been asserted. The REA model returned the user-expected results for five out of seven queries. We identify some challenges of implementing complete homology queries due to limitations of OWL reasoning. This work lays the foundation for homology reasoning to be incorporated into other ontology-based tools, such as those that enable synthetic supermatrix construction and candidate gene discovery. [Homology; ontology; anatomy; morphology; evolution; knowledgebase; phenoscape.]

Proteins with Spectrin Motifs Which Do Not Belong to the Spectrin-α-Actinin- Dystrophin Family

Using several consensus sequences for the 106 amino acid residue α-spectrin repeat segment as probes we searched animal sequence databases using the BLAST program in order to find proteins revealing limited, but significant similarity to spectrin. Among many spectrins and proteins from the spectrin-α-actinin-dystrophin family as well as sequences showing a rather high degree of similarity in very short stretches, we found seven homologous animal sequences of low overall similarity to spectrin but showing the presence of one or more spectrin-repeat motifs. The homology relationship of these sequences to α-spectrin was further analysed using the SEMIHOM program. Depending on the probe, these segments showed the presence of 6 to 26 identical amino acid residues and a variable number of semihomologous residues. Moreover, we found six protein sequences, which contained a sequence fragment sharing the SH3 (sarc homology region 3) domain homology of 42-59% similarity. Our data indicate the occurrence of motifs of significant homology to α-spectrin repeat segments among animal proteins, which are not classical members of the spectrin-α- actinin-dystrophin family. This might indicate that these segments together with the SH3 domain motif are conserved in proteins which possibly at the early stage of evolution were close cognates of spectrin-α-actinin-dystrophin progenitors but then evolved separately.

Homology of chromosomes of Triticum macha Dek. et Men. and Triticum aestivum L. as shown with the help of genetic markers

Inheritance of the storage protein (gliadin and glutenin) genes of Triticum macha Dek. et Men. and their allelism to Triticum aestivum L. genes have been studied. A close homology of at least chromosomes 1A and 1B of the two species has been found. Results confirm a very close relationship between T. macha and T. aestivum.Key words: seed storage proteins, genetic analysis, chromosome homology, relationship of Triticum macha Dek. et Men. and Triticum aestivum L.

Regulatory mechanisms in cell-mediated immune responses. II. A genetically restricted suppressor of mixed lymphocyte reactions released by alloantigen-activated spleen cells.

The mechanism of alloantigen-activated spleen cell suppression of mixed lymphocyte reaction (MLR) is explored in this report. Activated murine suppressor spleen cells elaborated a soluble noncytotoxic factor which suppressed MLR responses by 55-95%. Generation of suppressor factor required both in vivo alloantigen sensitization and specific in vitro restimulation. Suppressor factor was not produced by activated spleen cells which had been treated with anti-Thy-1.2 serum and complement. Antigenic specificity toward alloantigens of the stimulator cells was not demonstrable. In contrast, suppressor factor effectively inhibited MLR response only of responder cells of those strains that shared the D-end and the I-C subregion of the H-2 complex with the cells producing suppressor factor. Therefore, active suppression appears to require an MHC-directed homology relationship between regulating and responder cells in MLR.