Sentence examples for genes we generated from inspiring English sources

We considered the locust protein coding genes we generated as a locust core gene set for the following reasons.

In order to understand the interaction between different genes, we generated common networks using Ingenuity Pathway Analysis IPAA) software.

To identify endogeneous brain protective genes, we generated a retroviral cDNA expression library from primary cortical neurons preconditioned with OGD and conducted a functional cloning screen for protective molecules (Fig. 2).

To determine the sub-cellular location of the other 15 genes, we generated GFP-tagged versions of the proteins, expressed them during embryogenesis, and performed live imaging of the epidermis at stage 15 (dorsal closure).

To investigate whether the DNA-binding function of AmphiVent1 homeodomain is critical for the downregulation of both AmphiGoosecoid and AmphiChordin genes, we generated two mutants, AmphiVent1(R53andAmphiVent1ent1(N51Q), respectively, that contain point mutations in the DNA-binding helix of the homeodomain.

To identify RVE8 target genes, we generated a line with rapidly inducible RVE8 activity.

Finally, in order to gain a global understanding of the novel candidate genes, we generate a series of gene co-expression networks.

To confirm LOC_Os05g02730 is the GLR1 gene, we generated transgenic plants in a pubescence japonica variety Nipponbare background by the RNA interference (RNAi) method (Figure 4a).

To identify the Z3 gene, we generated a mapping population of 1547 F2 plants from a cross between the z3 mutant (japonica) and Milyang23 (an indica/japonica hybrid).

To further evaluate the potential use of the GNS4 gene, we generated transgenic lines using Wuyunjing 7 (WYJ7) as the recipient parent.

To understand what determines codon choices across a gene, we generated 12,726 in situ codon mutants in the Escherichia coli essential gene infA and measured their fitness by combining multiplex automated genome engineering mutagenesis with amplicon deep sequencing (MAGE-seq).