* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download Cross-Species Comparison of Regional Gene
Human–animal hybrid wikipedia , lookup
Human genetic variation wikipedia , lookup
Therapeutic gene modulation wikipedia , lookup
Microevolution wikipedia , lookup
History of genetic engineering wikipedia , lookup
Epigenetics of diabetes Type 2 wikipedia , lookup
Ridge (biology) wikipedia , lookup
Genome evolution wikipedia , lookup
Epigenetics of human development wikipedia , lookup
Genome (book) wikipedia , lookup
Genomic imprinting wikipedia , lookup
Long non-coding RNA wikipedia , lookup
Nutriepigenomics wikipedia , lookup
Designer baby wikipedia , lookup
Artificial gene synthesis wikipedia , lookup
Epigenetics of neurodegenerative diseases wikipedia , lookup
Gene expression programming wikipedia , lookup
Gene expression profiling wikipedia , lookup
Paper Review on Crossspecies Microarray Comparison Hong Lu 2008-10-14 Title: Conservation of Regional Gene Expression in Mouse and Human Brain Authors: Strand AD, Olson JM., et.al Year: 2007 Journal: PLoS genetics Purpose In-species comparison: To find the differences to distinguish resistant and sensitive tissues and cell types. Cross-species comparison: To provide a framework to explore the ability of mouse to model diseases of the human brain. Materials Persons Human Group I Group II Tissue 3: caudate, cerebellum, motor cortex 2: caudate cerebellum man 8 7 15 woman 4 2 6 Total 12 9 21 12 x 3 = 36 9 x 2 = 18 54 Range 36 ~ 77 22 ~ 72 22 ~ 77 Mean 58 49 54 Total Slides Age Affymetrix HG-U133A Probesets # 22,283 Total Sample Species Human Mouse(C57BL) Tissue 3 caudate, cerebellum, motor cortex 3 caudate, cerebellum, motor cortex Male 8 1 Female 4 5 Total 12 6 12 x 3 = 36 6 x 3 = 18 Range 36 ~ 77 (years) 35 (days) Mean 58 (years) 35 (days) Affymetrix HG-U133A MOE_430A_2 Probesets # 22,283 22,690 Total Slides Age Microarray analysis 1) Normalize the CEL files with Robust Multiplearray Average (RMA). 2) Fit a linear model for each of three pairs with LIMMA (bioconductor package) gene expression ≈ donor + tissue type • Caudate/Cerebellum • BA4 Cortex/Cerebellum • BA4 Cortex/Caudate 3) Get log ratio, paired t-statistics and p-values Sample result (human) Score Caudate/Cerebellum t P.value … … Caudate Cerebellum Motor cortex Probeset ID Log Ratio 106.05 -89.15 -16.9 215241_at 6.08 65.1 1.65E-21 … 103.2 -62.01 -41.19 220313_at 5.95 71.9 3.13E-22 … 93.7 -51.66 -42.04 207307_at 5.04 71.9 3.16E-22 … Caudate score = t-score(Caudate/Cerebellum) + t-score(Caudate/BA4 Cortex) Different Regions of the Brain Show Many Statistically Significant Differentially Expressed Genes To select sets of genes whose expression was highly enriched in one of the three regions Caudate Cerebellum BA4 Cortex 1) p < 0.001 and log ratio ≥ 1 in both relevant pair-wise comparisons. 2) The log ratios of the two relevant comparisons were summed, such as log2(BA4/caudate) + log2(BA4/cerebellum) would be candidate BA4 genes 3) Order sum of log ratios 4) if summed regional score >2 in more than one region, probesets were culled from the list. Table 3:Selected Regionally Enriched Genes in Human and Mouse Brain Tissues Gene Expression Variation between Tissues and Individuals gene expression ≈ donor + tissue type Within-tissue variance VS Between-tissue variance The variance for a probeset, across n samples, was calculated by where xi is the RMA signal for probeset i on array n. The between-tissue variability was greater for 89% of the human probesets and 85% of the mouse probesets. Conclusion: Compared to expression dictated by regional identity, age and gender appear to have effects of small magnitude or of large magnitude on a small fraction of genes, even in humans. Cross-Species Comparison of Regional Gene Expression What’s the relationship between mouse probesets and human probesets? ENSEMBL Mouse probesets Mouse ENSEMBL identities (Example: 1415688_at) Human probesets Human ENSEMBL identities (209141_at) dN/dS dN (number of nonsynonymous substitutions / number of nonsynonymous sites) dS (number of synonymous substitutions / number of synonymous sites) dN/dS was generated using the codeml (PAML package, pair-wise Maximum Likelihood Method) with F3 × 4 codon evolution model Pick up 2,998 one-to-one orthologus pairs. Compute normalized Euclidian distance between all possible nonself pairs of tissues. where there are g probesets and x and y are any two mouse or human samples. Euclidian distances between regions were calculated using the mean RMA probeset signals for each tissue. Conclusion: Orthologous Brain Regions between Species Are More Similar to Each Other than to Different Regions within a Species Analysis of GO categories Human: 70.6% of the probesets had an assigned GO category . Mouse: 66.2% of the probesets had an assigned GO category. For each GO category, The total number of probes in that category (a) VS The number of probes appearing on a list of differentially expressed probes (p < 0.05) (b) If a or b < 10 Fisher's exact test Otherwise Pearson chi-square To detect which category is over-represented. Conclusion: Mouse and Human Brain Regions Share a Higher Number of Overrepresented Functional Groups than Would Be Expected by Chance Relationships between Tissue-Specific Expression, Conservation of Sequence, and Conservation of Expression (A) X-axis: dN/dS ratios, least conserved (left) to most conserved (right). Y-axis: Correlation coefficient between human and mouse log ratios. (B) X-axis: The percent nucleotide identity, low (left) to high (right). Y-axis: Correlation coefficient between human and mouse log ratios. Conclusion: Genes with High Variance across Tissues Have Greater Conservation of Nucleotide Sequence Conclusion 1) In-species comparison: The different brain regions have distinctly different expression profiles. 2) Cross-species comparison: Region-specific genes are conserved at both the sequence and gene expression levels. (positive correlated) Advantage and Shortage? Thanks