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Biology subjects

Banf, M.

Publications and source records attributed to Banf, M..

2 recordsLinked to original sources

Phenotypic variation in maize can be largely explained by genetic variation at transcription factor binding sites

Comprehensive maps of functional variation at transcription factor (TF) binding sites (cis-elements) are crucial for elucidating how genotype shapes phenotype. Here we report the construction of a pan-cistrome of the maize leaf under well-watered and drought conditions. We quantified haplotype-specific TF footprints across a pan-genome of 25 maize hybrids and mapped over two-hundred thousand genetic variants (termed binding-QTL) linked to cis-element occupancy. Three lines of evidence support the functional significance of binding-QTL: i) they coincide with numerous known causative loci that regulate traits, including VGT1, Trehalase1, and the MITE transposon near ZmNAC111 under drought; ii) their footprint bias is mirrored between inbred parents and by ChIP-seq; iii) partitioning genetic variation across genomic regions demonstrates that binding-QTL capture the majority of heritable trait variation across [~]70% of 143 phenotypes. Our study provides a promising approach to make previously hidden cis-variation more accessible for genetic studies and multi-target engineering of complex traits.

genomics↗

METACLUSTERplus - an R package for probabilistic inference and visualization of context-specific transcriptional regulation of biosynthetic gene clusters

Fungi and plants reveal widespread occurrences of metabolic enzymes co-located on the chromosome, some already characterized as being biosynthetic pathways for specialized metabolites, such as terpenes synthesizing enzyme clusters in Lotus japonicus and Arabidopsis thaliana. These clusters display context-specific co-expression of clustered enzymes, indicating a shared transcriptional response in a spatial and condition specific manner, and co-regulation due to promoter binding by shared transcription factors may be one way to facilitate coordinated expression. To enhance our understanding of context-specific transcriptional gene cluster regulation, we redefine and augment this probabilistic framework, labelled METACLUSTERplus, integrating gene expression compendia, context-specific annotations, biosynthetic gene cluster definitions, as well as gene regulatory network architectures. Further, it provides a set of appealing and intuitive visualizations of inferred results for analysis and publication. METACLUSTERplus is available at https://github.com/mbanf/MetaclusterPlus.

bioinformatics↗