Unfinished part of lecture 5. How to explain trans-linked gene. If there is a cis-linked gene in a locus, a straightforward explanation of the trans-linkages is that the sequence polymorphism in the eQTL affects the expression of the cis-linked gene first, and
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loci with only trans-linkages but no cis-linkages are detected.
that contain no cis-linked genes (details in the supplementary materials).
Focus on spots with more than 3 trans-linked genes.
Altogether 7 such linkage spots (corresponding to a total of 44 trans-linked genes ) are identified
respiration are linked to Chromosome XI: 235.0kb to 252.8kb (marker block 390-391)
HAP4, which encodes a transcription activator of respiratory genes is found in this locus
Genome-wide TF binding data shows that Hap4 binds the upstream regions of ATP5, ATP7, and ATP14
Z to calculate LA scores.
We look for marker blocks appearing multiple times in the short list of marker blocks with best LA scores (20 most positive and 20 most negative).
We further find out that HAP4 co-expresses well with these genes if the sequence of marker block 41 is inherited from RM strain.
Trait-trait dynamic interaction: 2D-trait eQTL mapping for genetic variation study. BMC Genomics 2008, 9:242 doi:10.1186/1471-2164-9-242
An Introduction to the
The Gene Ontology project provides a controlled vocabulary to describe gene and gene product attributes in any organism.
Transitive functional annotation by shortest-path analysis of gene expression dataPNAS | October 1, 2002 | vol. 99 | no. 20 | 12783-12788Xianghong Zhou*, Ming-Chih J. Kao*, and Wing Hung Wong
Current methods for the functional analysis of microarray gene expression data make the implicit assumption that genes withsimilar expression profiles have similar functions in cells. However,among genes involved in the same biological pathway, not all genepairs show high expression similarity. Here, we propose that transitiveexpression similarity among genes can be used as an importantattribute to link genes of the same biological pathway. Basedon large-scale yeast microarray expression data, we use the shortest-pathanalysis to identify transitive genes between two given genesfrom the same biological process. We find that not only functionallyrelated genes with correlated expression profiles are identifiedbut also those without. In the latter case, we compare our methodto hierarchical clustering, and show that our method can revealfunctional relationships among genes in a more precise manner.Finally, we show that our method can be used to reliably predictthe function of unknown genes from known genes lying on the sameshortest path. We assigned functions for 146 yeast genes thatare considered as unknown by the Saccharomyces Genome Databaseand by the Yeast Proteome Database. These genes constitute around5% of the unknown yeastORFome.
Study of coordinative gene expression at the biological process levelTianwei Yu , Wei Sun , Shinsheng Yuan and Ker-Chau LiBioinformatics 2005 21(18):3651-3657
ComponentD shows an extensively connected network of metabolic processesincluding four major categories: coenzyme metabolism, aminoacid/lipid metabolism, small molecule transport/homeostasisand polysaccharide metabolism/energy generation.
A :cell-cycle mechanism
B:coherent operation within the translation mechanism
C: features the proteintransport mechanism
we find a totalof 202 GO-term associations significant at level 0.025.
Less connections are found.
Section A features yeast\'s characteristic responses under stress.
Section B features a cluster of ribosome/protein synthesis terms, together with a group of closely related metabolic terms.
Boxplots showing the relationship between GO-graph distances and K–L distances.
Proportion of expressionally associated pairs versus GO-graph distance. The GO-graph distance between two terms is the length of the shortest path between them, considering all edges as bi-directional. The K–L distances were computed from cell-cycle data.