Pseudoallelism and Gene Evolution

: Enzymes are among the most studied biological molecules because better understanding enzymes structure and activity will shed more light on their biological processes and regulation; from a biotechnological point of view there are many examples of enzymes used with the aim to obtain new products and/or to make industrial processes less invasive towards the environment. Enzymes are known for their high specificity in the recognition of a substrate but considering the particular features of an increasing number of enzymes this is not completely true, in fact, many enzymes are active on different substrates: this ability is called enzyme promiscuity. Usually, promiscuous activities have significantly lower kinetic parameters than to that of primary activity, but they have a crucial role in gene evolution. It is accepted that gene duplication followed by sequence divergence is considered a key evolutionary mechanism to generate new enzyme functions. In this way, promiscuous activities are the starting point to increase a secondary activity in the main activity and then get a new enzyme. The primary activity can be lost or reduced to a promiscuous activity. In this review we describe the differences between substrate and enzyme promiscuity, and its rule in gene evolution. From a practical point of view the knowledge of promiscuity can facilitate the in vitro progress of proteins engineering, both for biomedical and industrial applications. In particular, we report cases regarding esterases, phosphotriesterases and cytochrome P450.

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An Analytical Model of Gene Evolution with 9 Mutation Parameters: An Application to the Amino Acids Coded by the Common Circular Code

Bulletin of Mathematical Biology ◽

10.1007/s11538-006-9147-z ◽

2006 ◽

Vol 69 (2) ◽

pp. 677-698 ◽

Cited By ~ 12

Author(s):

Christian J. Michel

Keyword(s):

Amino Acids ◽

Analytical Model ◽

Gene Evolution ◽

The Common ◽

Circular Code

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Lie symmetry analysis of a stochastic gene evolution in double-chain deoxyribonucleic acid system

Waves in Random and Complex Media ◽

10.1080/17455030.2020.1871109 ◽

2021 ◽

pp. 1-15

Author(s):

R. Saleh ◽

S. M. Mabrouk ◽

Abdul-Majid Wazwaz

Keyword(s):

Deoxyribonucleic Acid ◽

Gene Evolution ◽

Lie Symmetry ◽

Symmetry Analysis ◽

Acid System ◽

Lie Symmetry Analysis ◽

Double Chain

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Organization, Expression and Evolution of a Disease Resistance Gene Cluster in Soybean

Genetics ◽

10.1093/genetics/162.4.1961 ◽

2002 ◽

Vol 162 (4) ◽

pp. 1961-1977

Author(s):

Michelle A Graham ◽

Laura Fredrick Marek ◽

Randy C Shoemaker

Keyword(s):

Disease Resistance ◽

Resistance Gene ◽

Resistance Genes ◽

Developmental Stages ◽

Gene Evolution ◽

Pcr Amplification ◽

Disease Resistance Genes ◽

Disease Resistance Gene ◽

R Genes ◽

Specific Primers

Abstract PCR amplification was previously used to identify a cluster of resistance gene analogues (RGAs) on soybean linkage group J. Resistance to powdery mildew (Rmd-c), Phytophthora stem and root rot (Rps2), and an ineffective nodulation gene (Rj2) map within this cluster. BAC fingerprinting and RGA-specific primers were used to develop a contig of BAC clones spanning this region in cultivar “Williams 82” [rps2, Rmd (adult onset), rj2]. Two cDNAs with homology to the TIR/NBD/LRR family of R-genes have also been mapped to opposite ends of a BAC in the contig Gm_Isb001_091F11 (BAC 91F11). Sequence analyses of BAC 91F11 identified 16 different resistance-like gene (RLG) sequences with homology to the TIR/NBD/LRR family of disease resistance genes. Four of these RLGs represent two potentially novel classes of disease resistance genes: TIR/NBD domains fused inframe to a putative defense-related protein (NtPRp27-like) and TIR domains fused inframe to soybean calmodulin Ca2+-binding domains. RT-PCR analyses using gene-specific primers allowed us to monitor the expression of individual genes in different tissues and developmental stages. Three genes appeared to be constitutively expressed, while three were differentially expressed. Analyses of the R-genes within this BAC suggest that R-gene evolution in soybean is a complex and dynamic process.

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