Gene synthesis design: a pythonic approach.

Researchers often need to synthesize genes of interest in this era of synthetic biology. Gene synthesis by PCR assembly of multiple DNA fragments is a quick and economical method that is widely applied. Up to now, there have been a few software solutions for designing fragments in gene synthesis. However, some of these software solutions use programming languages that are not popular now, other software products are commercial or require users to visit servers. In this study, we propose a Python program to design DNA fragments for gene synthesis. The algorithm is designed to meet the experimental needs. Also, the source code with detailed annotation is freely available for all users. Furthermore, the feasibility of the algorithm and the program is validated by experiments. Our program can be useful for the design of gene synthesis in the labs and help the study of gene structure and function.

A Python script to design primers for overlap extension PCR to ligate two DNA fragments.

Ligating two or more DNA fragments is a regular operation for the subcloning and the engineering of vectors. The overlap extension PCR serves as a straightforward method to solve this issue. However, it takes a relatively long time to design the appropriate overlapping primers and the primers for the full-length sequence, and there has not been a professional offline software for such kind of primer design. Here, we propose a Python script to search, calculate and sort thousands of combinations of primers for users according to the predefined parameters. The results of script running and experimental validation show that this script is capable of generating the optimal pairs of primers based on the proper melting temperatures and lengths of the primers, which facilitates gene modification in research.

De novo assembly of the complete mitochondrial genome of sweet potato (Ipomoea batatas [L.] Lam) revealed the existence of homologous conformations generated by the repeat-mediated recombination.

Sweet potato (Ipomoea batatas [L.] Lam) is an important food crop, an excellent fodder crop, and a new type of industrial raw material crop. The lack of genomic resources could affect the process of industrialization of sweet potato. Few detailed reports have been completed on the mitochondrial genome of sweet potato. In this research, we sequenced and assembled the mitochondrial genome of sweet potato and investigated its substructure. The mitochondrial genome of sweet potato is 270,304 bp with 23 unique core genes and 12 variable genes. We detected 279 pairs of repeat sequences and found that three pairs of direct repeats could mediate the homologous recombination into four independent circular molecules. We identified 70 SSRs in the whole mitochondrial genome of sweet potato. The longest dispersed repeat in mitochondrial genome was a palindromic repeat with a length of 915 bp. The homologous fragments between the chloroplast and mitochondrial genome account for 7.35% of the mitochondrial genome. We also predicted 597 RNA editing sites and found that the rps3 gene was edited 54 times, which occurred most frequently. This study further demonstrates the existence of multiple conformations in sweet potato mitochondrial genomes and provides a theoretical basis for the evolution of higher plants and cytoplasmic male sterility breeding.

A Python script to merge Sanger sequences.

Merging Sanger sequences is frequently needed during the gene cloning process. In this study, we provide a Python script that is able to assemble multiple overlapping Sanger sequences. The script utilizes the overlapping regions within the tandem Sanger sequences to merge the Sanger sequences. The results demonstrate that the script can produce the merged sequence from the input Sanger sequences in a single run. The script offers a simple and free method for merging Sanger sequences and is useful for gene cloning.

A python script to design site-directed mutagenesis primers.

Primer design is essential to conduct whole plasmid site-directed mutagenesis for protein study. Traditionally, primers of mutagenesis are designed manually that is time-consuming and fallible. Here, we present a Python script for searching primers by presetting parameters of nucleotide composition and percentage of guanine-cytosine (GC content). The running results showed that the script is able to search primers with mutations of target residue automatically. This script may facilitate primer design for whole plasmid site-directed mutagenesis and aid protein mutant construction.