MOESM6 of A quantitative image analysis pipeline for the characterization of filamentous fungal morphologies as a tool to uncover targets for morphology engineering: a case study using aplD in Aspergillus niger

Additional file 6. Functional predictions derived from gene co-expression network analysis support a role of A. niger aplD in endosomal transport and filamentous growth. Networks were previously calculated from over 300 micro-array experiments, with co-expression Spearman co-efficient values above 0.7 considered highly stringent and robust to aid gene functional predictions. The aplD gene co-expression network passing a co-efficient threshold of 0.7 was retrieved from FungiDB (n = 109 genes), and a selection of enriched GO-terms are reported. GO enrichment in the alp4 subnetwork cohort was calculated relative to the A. niger genome as a whole using default parameters in FungiDB. Enriched GO-terms were considered statistically significant when Benjamini-Hochberg false discovery correction p-value >0.05.

附加文件6：由基因共表达网络分析得到的功能预测结果，佐证了黑曲霉（A. niger）aplD基因在内体运输与菌丝生长过程中的功能。此前，研究人员基于超过300组微阵列实验构建了共表达网络，其中Spearman相关系数高于0.7的共表达关联被认定为严格且可靠的指标，用于辅助基因功能预测。我们从真菌数据库（FungiDB）中获取了满足0.7相关系数阈值的aplD基因共表达网络（共包含109个基因），并列出了部分富集的基因本体（GO）术语。针对alp4子网集群的GO富集分析，以黑曲霉全基因组作为背景参照，通过真菌数据库（FungiDB）的默认参数完成计算。当经Benjamini-Hochberg错误发现率校正后的P值大于0.05时，所富集的GO术语被认为具有统计学显著性。