A ABCA9 ALYREF ATIC CCDC28A CDC6 CDC7 CDCA7 Acidaminococcus Bilophila Butyricimonas Christensenellacese Clostridium obacterium Oscillospira Pseudomonas Sutterella Veillonella Ruminococcaceae B TAT ZNHITS ABCAB GINS2 CCDC28A PAICS CDCA7 Butyricimonas- Bilopha GINS1 EJF3J GENT4 TMEM97 OPP10 PTGFR LOR Haemophilus Clostridium Acidaminococcus UCP3 FAM111B Veillonella 0.75 MCM4 KIAREL3 MON1 ZC3H12A TFAM UNG TEX10 CMIP Christensencaceae DPP10 CDC6 Ruminococcaceae DUOX2 DUOXA2 EIF3J 0.5 Pseudomonas LCN2 Fusobacterium DUOXA2 ATIC LAPPRC MUCSAC, FAM111B RPLP2 CDC7 CMIP FAM120C TRHDE GCNT4 HELLS NUDCD1 Oscillospira DUOX2 TICAM1 GINS1 FAM120C GINS2 0.25 NUDT14 GSTO1 NAPSA HELLS ILDR1 KIRREL3 LCN2 LRPPRC MCM4 MDN1 MRPL17 MUCSAC NAPSA NUDCD1 NUDT14 PAICS PPP1R14B PTGFR RPLP2 SESN3 TAT TBX10 TFAM 0 -0.25 -0.5 TICAM1 TMEM97 TRHDE UCP3 UNG ZC3H12A ZNHIT6 -0.75 ZNHIT6 C DUOX2 2.00 1.75 1.50 1.25 rho=-0.675,q=0.083 Christensenellaceae rho-0.759.q=0.045 DUOXA2 LCN2 rho=-0.772.q=0.04 Ruminococcaceae rho-0.698.q=0.082 . -1 -5.0 -2.5 Butyricimonas 0.0 -75-50-25 DO 25 5.0 Veillonella Fig. 3 Interactions between genes associated with colorectal cancer and gut mucosal microbes. a Correlation plot depicting gene-microbe correlations. Color and size of the squares indicate the magnitude of the correlation, asterisks indicate significance of correlation (** indicates q value < 0.05 and indicates q value <0.1). b Network visualizing significant gene-microbe correlations (solid edges, q value <0.1) and significant microbe-microbe correlations (dashed edges, SparCC |R|>=0.1 and p value <0.05). Blue edges indicate positive correlation and red edges indicate negative correlation. Edge thickness represents the strength of the correlation. c Scatterplots depicting pattern of grouping by cystic fibrosis (red) and healthy (blue) samples in a few representative gene-microbe correlations, where the strength of correlation (Spearman rho) and significance (q) is indicated at the top of each plot and dashed edges represent microbe-microbe correla- tions. This subnetwork of microbe-microbe correlations depicts correlated abundance changes in the microbiome as a function of their presence (Fig. 3b, dashed edges). For instance, Bilophila and Butyricimonas are both de- pleted in CF (q value < 0.05), and the abundance of the two genera is also correlated across individuals (SparCC R-05 pseudo-n value-0.04) On the other hand solid edges), microbial nodes have more edges on aver- age compared to genes, where Christensenellaceae and Clostridium formed distinct hubs in the network. This potentially implies that these microbes and their path- ways are shared across multiple GI cancer-associated genes. Of note, Bilophila, Clostridium, and Pseudomonas are mostly negatively correlated with Gl cancer genes, while Haemophilus Oscillosnira Veillonella Eusobacter MacBook Pro

Biology: The Unity and Diversity of Life (MindTap Course List)
15th Edition
ISBN:9781337408332
Author:Cecie Starr, Ralph Taggart, Christine Evers, Lisa Starr
Publisher:Cecie Starr, Ralph Taggart, Christine Evers, Lisa Starr
Chapter39: Digestion And Nutrition
Section: Chapter Questions
Problem 11SQ
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Question
what is figure 3B characterizing?
A
ABCA9
ALYREF
ATIC
CCDC28A
CDC6
CDC7
CDCA7
Acidaminococcus
Bilophila
Butyricimonas
Christensenellacese
Clostridium
obacterium
Oscillospira
Pseudomonas
Sutterella
Veillonella
Ruminococcaceae
B
TAT ZNHITS
ABCAB
GINS2
CCDC28A
PAICS
CDCA7
Butyricimonas-
Bilopha
GINS1
EJF3J
GENT4
TMEM97
OPP10
PTGFR
LOR
Haemophilus Clostridium
Acidaminococcus
UCP3
FAM111B
Veillonella
0.75
MCM4
KIAREL3
MON1
ZC3H12A
TFAM
UNG
TEX10
CMIP
Christensencaceae
DPP10
CDC6
Ruminococcaceae
DUOX2
DUOXA2
EIF3J
0.5
Pseudomonas LCN2
Fusobacterium DUOXA2
ATIC
LAPPRC
MUCSAC,
FAM111B
RPLP2
CDC7
CMIP
FAM120C
TRHDE
GCNT4
HELLS NUDCD1
Oscillospira
DUOX2 TICAM1
GINS1
FAM120C
GINS2
0.25
NUDT14
GSTO1
NAPSA
HELLS
ILDR1
KIRREL3
LCN2
LRPPRC
MCM4
MDN1
MRPL17
MUCSAC
NAPSA
NUDCD1
NUDT14
PAICS
PPP1R14B
PTGFR
RPLP2
SESN3
TAT
TBX10
TFAM
0
-0.25
-0.5
TICAM1
TMEM97
TRHDE
UCP3
UNG
ZC3H12A
ZNHIT6
-0.75
ZNHIT6
C
DUOX2
2.00
1.75
1.50
1.25
rho=-0.675,q=0.083
Christensenellaceae
rho-0.759.q=0.045
DUOXA2
LCN2
rho=-0.772.q=0.04
Ruminococcaceae
rho-0.698.q=0.082
.
-1
-5.0 -2.5
Butyricimonas
0.0
-75-50-25 DO 25 5.0
Veillonella
Fig. 3 Interactions between genes associated with colorectal cancer and gut mucosal microbes. a Correlation plot depicting gene-microbe
correlations. Color and size of the squares indicate the magnitude of the correlation, asterisks indicate significance of correlation (** indicates q
value < 0.05 and indicates q value <0.1). b Network visualizing significant gene-microbe correlations (solid edges, q value <0.1) and significant
microbe-microbe correlations (dashed edges, SparCC |R|>=0.1 and p value <0.05). Blue edges indicate positive correlation and red edges
indicate negative correlation. Edge thickness represents the strength of the correlation. c Scatterplots depicting pattern of grouping by cystic
fibrosis (red) and healthy (blue) samples in a few representative gene-microbe correlations, where the strength of correlation (Spearman rho) and
significance (q) is indicated at the top of each plot
and dashed edges represent microbe-microbe correla-
tions. This subnetwork of microbe-microbe correlations
depicts correlated abundance changes in the microbiome
as a function of their presence (Fig. 3b, dashed edges).
For instance, Bilophila and Butyricimonas are both de-
pleted in CF (q value < 0.05), and the abundance of the
two genera is also correlated across individuals (SparCC
R-05 pseudo-n value-0.04) On the other hand
solid edges), microbial nodes have more edges on aver-
age compared to genes, where Christensenellaceae and
Clostridium formed distinct hubs in the network. This
potentially implies that these microbes and their path-
ways are shared across multiple GI cancer-associated
genes. Of note, Bilophila, Clostridium, and Pseudomonas
are mostly negatively correlated with Gl cancer genes,
while Haemophilus Oscillosnira Veillonella Eusobacter
MacBook Pro
Transcribed Image Text:A ABCA9 ALYREF ATIC CCDC28A CDC6 CDC7 CDCA7 Acidaminococcus Bilophila Butyricimonas Christensenellacese Clostridium obacterium Oscillospira Pseudomonas Sutterella Veillonella Ruminococcaceae B TAT ZNHITS ABCAB GINS2 CCDC28A PAICS CDCA7 Butyricimonas- Bilopha GINS1 EJF3J GENT4 TMEM97 OPP10 PTGFR LOR Haemophilus Clostridium Acidaminococcus UCP3 FAM111B Veillonella 0.75 MCM4 KIAREL3 MON1 ZC3H12A TFAM UNG TEX10 CMIP Christensencaceae DPP10 CDC6 Ruminococcaceae DUOX2 DUOXA2 EIF3J 0.5 Pseudomonas LCN2 Fusobacterium DUOXA2 ATIC LAPPRC MUCSAC, FAM111B RPLP2 CDC7 CMIP FAM120C TRHDE GCNT4 HELLS NUDCD1 Oscillospira DUOX2 TICAM1 GINS1 FAM120C GINS2 0.25 NUDT14 GSTO1 NAPSA HELLS ILDR1 KIRREL3 LCN2 LRPPRC MCM4 MDN1 MRPL17 MUCSAC NAPSA NUDCD1 NUDT14 PAICS PPP1R14B PTGFR RPLP2 SESN3 TAT TBX10 TFAM 0 -0.25 -0.5 TICAM1 TMEM97 TRHDE UCP3 UNG ZC3H12A ZNHIT6 -0.75 ZNHIT6 C DUOX2 2.00 1.75 1.50 1.25 rho=-0.675,q=0.083 Christensenellaceae rho-0.759.q=0.045 DUOXA2 LCN2 rho=-0.772.q=0.04 Ruminococcaceae rho-0.698.q=0.082 . -1 -5.0 -2.5 Butyricimonas 0.0 -75-50-25 DO 25 5.0 Veillonella Fig. 3 Interactions between genes associated with colorectal cancer and gut mucosal microbes. a Correlation plot depicting gene-microbe correlations. Color and size of the squares indicate the magnitude of the correlation, asterisks indicate significance of correlation (** indicates q value < 0.05 and indicates q value <0.1). b Network visualizing significant gene-microbe correlations (solid edges, q value <0.1) and significant microbe-microbe correlations (dashed edges, SparCC |R|>=0.1 and p value <0.05). Blue edges indicate positive correlation and red edges indicate negative correlation. Edge thickness represents the strength of the correlation. c Scatterplots depicting pattern of grouping by cystic fibrosis (red) and healthy (blue) samples in a few representative gene-microbe correlations, where the strength of correlation (Spearman rho) and significance (q) is indicated at the top of each plot and dashed edges represent microbe-microbe correla- tions. This subnetwork of microbe-microbe correlations depicts correlated abundance changes in the microbiome as a function of their presence (Fig. 3b, dashed edges). For instance, Bilophila and Butyricimonas are both de- pleted in CF (q value < 0.05), and the abundance of the two genera is also correlated across individuals (SparCC R-05 pseudo-n value-0.04) On the other hand solid edges), microbial nodes have more edges on aver- age compared to genes, where Christensenellaceae and Clostridium formed distinct hubs in the network. This potentially implies that these microbes and their path- ways are shared across multiple GI cancer-associated genes. Of note, Bilophila, Clostridium, and Pseudomonas are mostly negatively correlated with Gl cancer genes, while Haemophilus Oscillosnira Veillonella Eusobacter MacBook Pro
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