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vgainullin
/
xciting_data

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5
INTRODUCTION
0
null
null
17,088,291
null
We show that both long 3′-UTRs and introns located in the 3′-UTR act as NMD cis factors.
null
88
7,900
0
false
null
null
We show that both long 3′-UTRs and introns located in the 3′-UTR act as NMD cis factors.
true
true
true
true
true
1,285
5
INTRODUCTION
0
null
null
17,088,291
null
As both long 3′-UTR-based and intron-based PTC identification systems operate in plants as well as in animals, it is likely that these PTC definition systems already existed in the common ancestor of stem eukaryotes.
null
216
7,901
0
false
null
null
As both long 3′-UTR-based and intron-based PTC identification systems operate in plants as well as in animals, it is likely that these PTC definition systems already existed in the common ancestor of stem eukaryotes.
true
true
true
true
true
1,285
5
INTRODUCTION
0
null
null
17,088,291
null
We have also shown that tethering of UPF1 to either the 5′- or 3′-UTR causes a dramatic reduction of target mRNA levels, suggesting that in plants, UPF1 binds to the mRNA in a late, irreversible phase of NMD.
null
208
7,902
0
false
null
null
We have also shown that tethering of UPF1 to either the 5′- or 3′-UTR causes a dramatic reduction of target mRNA levels, suggesting that in plants, UPF1 binds to the mRNA in a late, irreversible phase of NMD.
true
true
true
true
true
1,285
0
DISCUSSION
1
54
[ "b54" ]
17,088,291
pmid-15448691|pmid-14690598|pmid-12609035
Transient assays have been efficiently used to analyse NMD in mammalian and Drosophila cells.
[ "54" ]
93
7,903
0
false
Transient assays have been efficiently used to analyse NMD in mammalian and Drosophila cells.
[]
Transient assays have been efficiently used to analyse NMD in mammalian and Drosophila cells.
true
true
true
true
true
1,286
0
DISCUSSION
1
54
[ "b54" ]
17,088,291
pmid-15448691|pmid-14690598|pmid-12609035
As transient NMD assays often require the expression of several different genes, and because agroinfiltration is the best method to co-express many different genes in plants (54), we have established an agroinfiltration-based transient plant NMD test system.
[ "54" ]
258
7,904
1
false
As transient NMD assays often require the expression of several different genes, and because agroinfiltration is the best method to co-express many different genes in plants, we have established an agroinfiltration-based transient plant NMD test system.
[ "54" ]
As transient NMD assays often require the expression of several different genes, and because agroinfiltration is the best method to co-express many different genes in plants, we have established an agroinfiltration-based transient plant NMD test system.
true
true
true
true
true
1,286
0
DISCUSSION
1
54
[ "b54" ]
17,088,291
pmid-15448691|pmid-14690598|pmid-12609035
We have shown that PTC-containing mRNAs accumulate to low levels relative to wild-type controls and that the levels of PTC-containing mRNAs are selectively increased by cycloheximide treatment or by co-expressing UPF1DN, a dominant-negative mutant of plant UPF1 (Figures 2 and 3).
[ "54" ]
280
7,905
0
false
We have shown that PTC-containing mRNAs accumulate to low levels relative to wild-type controls and that the levels of PTC-containing mRNAs are selectively increased by cycloheximide treatment or by co-expressing UPF1DN, a dominant-negative mutant of plant UPF1 (Figures 2 and 3).
[]
We have shown that PTC-containing mRNAs accumulate to low levels relative to wild-type controls and that the levels of PTC-containing mRNAs are selectively increased by cycloheximide treatment or by co-expressing UPF1DN, a dominant-negative mutant of plant UPF1 (Figures 2 and 3).
true
true
true
true
true
1,286
0
DISCUSSION
1
54
[ "b54" ]
17,088,291
pmid-15448691|pmid-14690598|pmid-12609035
These data indicate that in agroinfiltrated leaves PTC-containing mRNAs were targeted by NMD.
[ "54" ]
93
7,906
0
false
These data indicate that in agroinfiltrated leaves PTC-containing mRNAs were targeted by NMD.
[]
These data indicate that in agroinfiltrated leaves PTC-containing mRNAs were targeted by NMD.
true
true
true
true
true
1,286
0
DISCUSSION
1
54
[ "b54" ]
17,088,291
pmid-15448691|pmid-14690598|pmid-12609035
We think that this versatile transient NMD test system, in combination with UPF1DN co-expression and λN-boxB tethering assay systems can become useful tools to characterize plant NMD.
[ "54" ]
183
7,907
0
false
We think that this versatile transient NMD test system, in combination with UPF1DN co-expression and λN-boxB tethering assay systems can become useful tools to characterize plant NMD.
[]
We think that this versatile transient NMD test system, in combination with UPF1DN co-expression and λN-boxB tethering assay systems can become useful tools to characterize plant NMD.
true
true
true
true
true
1,286
1
DISCUSSION
0
null
null
17,088,291
pmid-15040442|pmid-16043493|pmid-15525991|pmid-16246174
Taking the advantage of the transient NMD test system, we have identified the cis elements of plant NMD.
null
104
7,908
0
false
null
null
Taking the advantage of the transient NMD test system, we have identified the cis elements of plant NMD.
true
true
true
true
true
1,287
1
DISCUSSION
0
null
null
17,088,291
pmid-15040442|pmid-16043493|pmid-15525991|pmid-16246174
We found that in plants stop codons are identified as PTC if the 3′-UTR is unusually long or if an intron is located in the 3′-UTR.
null
131
7,909
0
false
null
null
We found that in plants stop codons are identified as PTC if the 3′-UTR is unusually long or if an intron is located in the 3′-UTR.
true
true
true
true
true
1,287
2
DISCUSSION
1
30
[ "b30", "b33", "b8", "b17", "b19", "b55", "b9", "b8" ]
17,088,291
pmid-12672499|pmid-15145352|pmid-11118221|pmid-15608055|pmid-9644970|pmid-7891717|pmid-10882134|pmid-15525991|pmid-12881430|pmid-8104846|pmid-16622410|pmid-15525991|pmid-16723977|pmid-2152115|pmid-10758507|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16246174|pmid-15525991
Previous reports have shown that intronless mRNAs can be degraded by NMD in plants (30–33).
[ "30", "33", "8", "17", "19", "55", "9", "8" ]
91
7,910
0
false
Previous reports have shown that intronless mRNAs can be degraded by NMD in plants.
[ "30–33" ]
Previous reports have shown that intronless mRNAs can be degraded by NMD in plants.
true
true
true
true
true
1,288
2
DISCUSSION
1
30
[ "b30", "b33", "b8", "b17", "b19", "b55", "b9", "b8" ]
17,088,291
pmid-12672499|pmid-15145352|pmid-11118221|pmid-15608055|pmid-9644970|pmid-7891717|pmid-10882134|pmid-15525991|pmid-12881430|pmid-8104846|pmid-16622410|pmid-15525991|pmid-16723977|pmid-2152115|pmid-10758507|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16246174|pmid-15525991
Consistently we have found that intronless mRNAs are targeted by NMD if a PTC is introduced into the coding region or if stuffer sequences are cloned into their 3′-UTRs (Figures 2 and 3).
[ "30", "33", "8", "17", "19", "55", "9", "8" ]
187
7,911
0
false
Consistently we have found that intronless mRNAs are targeted by NMD if a PTC is introduced into the coding region or if stuffer sequences are cloned into their 3′-UTRs (Figures 2 and 3).
[]
Consistently we have found that intronless mRNAs are targeted by NMD if a PTC is introduced into the coding region or if stuffer sequences are cloned into their 3′-UTRs.
true
true
true
true
true
1,288
2
DISCUSSION
1
30
[ "b30", "b33", "b8", "b17", "b19", "b55", "b9", "b8" ]
17,088,291
pmid-12672499|pmid-15145352|pmid-11118221|pmid-15608055|pmid-9644970|pmid-7891717|pmid-10882134|pmid-15525991|pmid-12881430|pmid-8104846|pmid-16622410|pmid-15525991|pmid-16723977|pmid-2152115|pmid-10758507|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16246174|pmid-15525991
As we failed to identify DSE-like destabilizing sequences and because insertion of either bacterial or plant sequences into the 3′-UTR triggered NMD, we concluded that long 3′-UTR subjected intronless mRNAs to NMD in plants.
[ "30", "33", "8", "17", "19", "55", "9", "8" ]
224
7,912
0
false
As we failed to identify DSE-like destabilizing sequences and because insertion of either bacterial or plant sequences into the 3′-UTR triggered NMD, we concluded that long 3′-UTR subjected intronless mRNAs to NMD in plants.
[]
As we failed to identify DSE-like destabilizing sequences and because insertion of either bacterial or plant sequences into the 3′-UTR triggered NMD, we concluded that long 3′-UTR subjected intronless mRNAs to NMD in plants.
true
true
true
true
true
1,288
2
DISCUSSION
1
30
[ "b30", "b33", "b8", "b17", "b19", "b55", "b9", "b8" ]
17,088,291
pmid-12672499|pmid-15145352|pmid-11118221|pmid-15608055|pmid-9644970|pmid-7891717|pmid-10882134|pmid-15525991|pmid-12881430|pmid-8104846|pmid-16622410|pmid-15525991|pmid-16723977|pmid-2152115|pmid-10758507|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16246174|pmid-15525991
Moreover, we have shown that this effect was size-dependent, mRNAs with longer 3′-UTR were more effectively targeted by NMD than transcript with shorter 3′-UTR (Figure 3D and E).
[ "30", "33", "8", "17", "19", "55", "9", "8" ]
178
7,913
0
false
Moreover, we have shown that this effect was size-dependent, mRNAs with longer 3′-UTR were more effectively targeted by NMD than transcript with shorter 3′-UTR (Figure 3D and E).
[]
Moreover, we have shown that this effect was size-dependent, mRNAs with longer 3′-UTR were more effectively targeted by NMD than transcript with shorter 3′-UTR.
true
true
true
true
true
1,288
2
DISCUSSION
1
30
[ "b30", "b33", "b8", "b17", "b19", "b55", "b9", "b8" ]
17,088,291
pmid-12672499|pmid-15145352|pmid-11118221|pmid-15608055|pmid-9644970|pmid-7891717|pmid-10882134|pmid-15525991|pmid-12881430|pmid-8104846|pmid-16622410|pmid-15525991|pmid-16723977|pmid-2152115|pmid-10758507|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16246174|pmid-15525991
Long 3′-UTR could also trigger NMD in yeast, Drosophila, worm and mammalian cells (8,17–19,55).
[ "30", "33", "8", "17", "19", "55", "9", "8" ]
95
7,914
0
false
Long 3′-UTR could also trigger NMD in yeast, Drosophila, worm and mammalian cells.
[ "8,17–19,55" ]
Long 3′-UTR could also trigger NMD in yeast, Drosophila, worm and mammalian cells.
true
true
true
true
true
1,288
2
DISCUSSION
1
9
[ "b30", "b33", "b8", "b17", "b19", "b55", "b9", "b8" ]
17,088,291
pmid-12672499|pmid-15145352|pmid-11118221|pmid-15608055|pmid-9644970|pmid-7891717|pmid-10882134|pmid-15525991|pmid-12881430|pmid-8104846|pmid-16622410|pmid-15525991|pmid-16723977|pmid-2152115|pmid-10758507|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16246174|pmid-15525991
The faux UTR model of yeast NMD suggests that long 3′-UTR (and perhaps other unusual 3′-UTRs) causes aberrant translation termination and that aberrant termination leads to the formation of a functional NMD complex (9).
[ "30", "33", "8", "17", "19", "55", "9", "8" ]
219
7,915
1
false
The faux UTR model of yeast NMD suggests that long 3′-UTR (and perhaps other unusual 3′-UTRs) causes aberrant translation termination and that aberrant termination leads to the formation of a functional NMD complex.
[ "9" ]
The faux UTR model of yeast NMD suggests that long 3′-UTR (and perhaps other unusual 3′-UTRs) causes aberrant translation termination and that aberrant termination leads to the formation of a functional NMD complex.
true
true
true
true
true
1,288
2
DISCUSSION
1
30
[ "b30", "b33", "b8", "b17", "b19", "b55", "b9", "b8" ]
17,088,291
pmid-12672499|pmid-15145352|pmid-11118221|pmid-15608055|pmid-9644970|pmid-7891717|pmid-10882134|pmid-15525991|pmid-12881430|pmid-8104846|pmid-16622410|pmid-15525991|pmid-16723977|pmid-2152115|pmid-10758507|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16246174|pmid-15525991
As PTC-containing yeast mRNAs can be protected from NMD if PABP is tethered downstream of the stop codon, it is likely that long 3′-UTR causes aberrant termination by inhibiting the interaction of terminating ribosome with PABP (
[ "30", "33", "8", "17", "19", "55", "9", "8" ]
229
7,916
0
false
As PTC-containing yeast mRNAs can be protected from NMD if PABP is tethered downstream of the stop codon, it is likely that long 3′-UTR causes aberrant termination by inhibiting the interaction of terminating ribosome with PABP (
[]
As PTC-containing yeast mRNAs can be protected from NMD if PABP is tethered downstream of the stop codon, it is likely that long 3′-UTR causes aberrant termination by inhibiting the interaction of terminating ribosome with PABP (
true
true
false
true
false
1,288
2
DISCUSSION
1
30
[ "b30", "b33", "b8", "b17", "b19", "b55", "b9", "b8" ]
17,088,291
pmid-12672499|pmid-15145352|pmid-11118221|pmid-15608055|pmid-9644970|pmid-7891717|pmid-10882134|pmid-15525991|pmid-12881430|pmid-8104846|pmid-16622410|pmid-15525991|pmid-16723977|pmid-2152115|pmid-10758507|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16246174|pmid-15525991
Our findings that long 3′-UTR triggers NMD in plants and that this transcript destabilizing effect depends on the size of the 3′-UTR can be explained if the faux UTR model is valid for plant NMD.
[ "30", "33", "8", "17", "19", "55", "9", "8" ]
195
7,917
0
false
Our findings that long 3′-UTR triggers NMD in plants and that this transcript destabilizing effect depends on the size of the 3′-UTR can be explained if the faux UTR model is valid for plant NMD.
[]
Our findings that long 3′-UTR triggers NMD in plants and that this transcript destabilizing effect depends on the size of the 3′-UTR can be explained if the faux UTR model is valid for plant NMD.
true
true
true
true
true
1,288
2
DISCUSSION
1
30
[ "b30", "b33", "b8", "b17", "b19", "b55", "b9", "b8" ]
17,088,291
pmid-12672499|pmid-15145352|pmid-11118221|pmid-15608055|pmid-9644970|pmid-7891717|pmid-10882134|pmid-15525991|pmid-12881430|pmid-8104846|pmid-16622410|pmid-15525991|pmid-16723977|pmid-2152115|pmid-10758507|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16246174|pmid-15525991
Therefore, we suggest that aberrant translation termination also leads to NMD in plants and that increasing the distance between terminating ribosome and PABP results in aberrant termination.
[ "30", "33", "8", "17", "19", "55", "9", "8" ]
191
7,918
0
false
Therefore, we suggest that aberrant translation termination also leads to NMD in plants and that increasing the distance between terminating ribosome and PABP results in aberrant termination.
[]
Therefore, we suggest that aberrant translation termination also leads to NMD in plants and that increasing the distance between terminating ribosome and PABP results in aberrant termination.
true
true
true
true
true
1,288
3
DISCUSSION
1
56
[ "b56", "b57" ]
17,088,291
pmid-15901503|pmid-16141059|pmid-16289965|pmid-16280547|pmid-15496452
Introns could also act as NMD cis elements in plants.
[ "56", "57" ]
53
7,919
0
false
Introns could also act as NMD cis elements in plants.
[]
Introns could also act as NMD cis elements in plants.
true
true
true
true
true
1,289
3
DISCUSSION
1
56
[ "b56", "b57" ]
17,088,291
pmid-15901503|pmid-16141059|pmid-16289965|pmid-16280547|pmid-15496452
The finding that incorporation of Ls intron into the 3′-UTR of either the GFP or PHA-s transcripts subjects these mRNAs to NMD (Figure 4) supports this conclusion.
[ "56", "57" ]
163
7,920
0
false
The finding that incorporation of Ls intron into the 3′-UTR of either the GFP or PHA-s transcripts subjects these mRNAs to NMD (Figure 4) supports this conclusion.
[]
The finding that incorporation of Ls intron into the 3′-UTR of either the GFP or PHA-s transcripts subjects these mRNAs to NMD (Figure 4) supports this conclusion.
true
true
true
true
true
1,289
3
DISCUSSION
1
56
[ "b56", "b57" ]
17,088,291
pmid-15901503|pmid-16141059|pmid-16289965|pmid-16280547|pmid-15496452
Moreover, the effect of plant introns on mRNA stability is position-dependent.
[ "56", "57" ]
78
7,921
0
false
Moreover, the effect of plant introns on mRNA stability is position-dependent.
[]
Moreover, the effect of plant introns on mRNA stability is position-dependent.
true
true
true
true
true
1,289
3
DISCUSSION
1
56
[ "b56", "b57" ]
17,088,291
pmid-15901503|pmid-16141059|pmid-16289965|pmid-16280547|pmid-15496452
mRNAs carrying Ls intron 99 nt downstream of the stop codon were targeted by NMD, while transcripts carrying the same intron 28 nt downstream of the stop codon did not trigger NMD (Figure 4C and D).
[ "56", "57" ]
198
7,922
0
false
mRNAs carrying Ls intron 99 nt downstream of the stop codon were targeted by NMD, while transcripts carrying the same intron 28 nt downstream of the stop codon did not trigger NMD (Figure 4C and D).
[]
mRNAs carrying Ls intron 99 nt downstream of the stop codon were targeted by NMD, while transcripts carrying the same intron 28 nt downstream of the stop codon did not trigger NMD (Figure 4C and D).
false
true
true
true
false
1,289
3
DISCUSSION
1
56
[ "b56", "b57" ]
17,088,291
pmid-15901503|pmid-16141059|pmid-16289965|pmid-16280547|pmid-15496452
In mammals, introns located less than 50–55 nt downstream of the stop codon also fail to trigger NMD.
[ "56", "57" ]
101
7,923
0
false
In mammals, introns located less than 50–55 nt downstream of the stop codon also fail to trigger NMD.
[]
In mammals, introns located less than 50–55 nt downstream of the stop codon also fail to trigger NMD.
true
true
true
true
true
1,289
3
DISCUSSION
1
56
[ "b56", "b57" ]
17,088,291
pmid-15901503|pmid-16141059|pmid-16289965|pmid-16280547|pmid-15496452
As 3′-UTR located introns trigger NMD in a similar position-dependent manner in both plants and mammals, we suggest that in plants, like in mammals, EJC connects splicing and NMD.
[ "56", "57" ]
179
7,924
0
false
As 3′-UTR located introns trigger NMD in a similar position-dependent manner in both plants and mammals, we suggest that in plants, like in mammals, EJC connects splicing and NMD.
[]
As 3′-UTR located introns trigger NMD in a similar position-dependent manner in both plants and mammals, we suggest that in plants, like in mammals, EJC connects splicing and NMD.
true
true
true
true
true
1,289
3
DISCUSSION
1
56
[ "b56", "b57" ]
17,088,291
pmid-15901503|pmid-16141059|pmid-16289965|pmid-16280547|pmid-15496452
Indeed, the putative orthologs of most EJC components were identified in plants (56,57).
[ "56", "57" ]
88
7,925
0
false
Indeed, the putative orthologs of most EJC components were identified in plants.
[ "56,57" ]
Indeed, the putative orthologs of most EJC components were identified in plants.
true
true
true
true
true
1,289
3
DISCUSSION
1
56
[ "b56", "b57" ]
17,088,291
pmid-15901503|pmid-16141059|pmid-16289965|pmid-16280547|pmid-15496452
However, in plants, unlike in mammals, the 3′-UTR tethering of EJC proteins does not result in the decay of targeted mRNAs (Supplementary Figure 8).
[ "56", "57" ]
148
7,926
0
false
However, in plants, unlike in mammals, the 3′-UTR tethering of EJC proteins does not result in the decay of targeted mRNAs (Supplementary Figure 8).
[]
However, in plants, unlike in mammals, the 3′-UTR tethering of EJC proteins does not result in the decay of targeted mRNAs (Supplementary Figure 8).
true
true
true
true
true
1,289
3
DISCUSSION
1
56
[ "b56", "b57" ]
17,088,291
pmid-15901503|pmid-16141059|pmid-16289965|pmid-16280547|pmid-15496452
Therefore further experiments are required to prove that plant EJCs are directly involved in NMD.
[ "56", "57" ]
97
7,927
0
false
Therefore further experiments are required to prove that plant EJCs are directly involved in NMD.
[]
Therefore further experiments are required to prove that plant EJCs are directly involved in NMD.
true
true
true
true
true
1,289
4
DISCUSSION
1
35
[ "b35", "b35", "b36", "b58" ]
17,088,291
pmid-15951220|pmid-8980474|pmid-12672499|pmid-16098107|pmid-16540482|pmid-16813578|pmid-16540482|pmid-16740149|pmid-2152115|pmid-10758507|pmid-11244118|pmid-15331098|pmid-15546357|pmid-15331098|pmid-15331098|pmid-15546357|pmid-16116435
Our data that introns can act as NMD cis elements in plants are apparently conflicting with previous studies.
[ "35", "35", "36", "58" ]
109
7,928
0
false
Our data that introns can act as NMD cis elements in plants are apparently conflicting with previous studies.
[]
Our data that introns can act as NMD cis elements in plants are apparently conflicting with previous studies.
true
true
true
true
true
1,290
4
DISCUSSION
1
35
[ "b35", "b35", "b36", "b58" ]
17,088,291
pmid-15951220|pmid-8980474|pmid-12672499|pmid-16098107|pmid-16540482|pmid-16813578|pmid-16540482|pmid-16740149|pmid-2152115|pmid-10758507|pmid-11244118|pmid-15331098|pmid-15546357|pmid-15331098|pmid-15331098|pmid-15546357|pmid-16116435
It has been suggested that introns do not trigger NMD in barley, because mRNAs containing introns downstream of the PTC and the control transcripts accumulated to comparable levels (35).
[ "35", "35", "36", "58" ]
186
7,929
1
false
It has been suggested that introns do not trigger NMD in barley, because mRNAs containing introns downstream of the PTC and the control transcripts accumulated to comparable levels.
[ "35" ]
It has been suggested that introns do not trigger NMD in barley, because mRNAs containing introns downstream of the PTC and the control transcripts accumulated to comparable levels.
true
true
true
true
true
1,290
4
DISCUSSION
1
35
[ "b35", "b35", "b36", "b58" ]
17,088,291
pmid-15951220|pmid-8980474|pmid-12672499|pmid-16098107|pmid-16540482|pmid-16813578|pmid-16540482|pmid-16740149|pmid-2152115|pmid-10758507|pmid-11244118|pmid-15331098|pmid-15546357|pmid-15331098|pmid-15331098|pmid-15546357|pmid-16116435
However, the transcript which was used as a control in that study also carried a PTC, therefore the control transcript could be also targeted by NMD.
[ "35", "35", "36", "58" ]
149
7,930
0
false
However, the transcript which was used as a control in that study also carried a PTC, therefore the control transcript could be also targeted by NMD.
[]
However, the transcript which was used as a control in that study also carried a PTC, therefore the control transcript could be also targeted by NMD.
true
true
true
true
true
1,290
4
DISCUSSION
1
35
[ "b35", "b35", "b36", "b58" ]
17,088,291
pmid-15951220|pmid-8980474|pmid-12672499|pmid-16098107|pmid-16540482|pmid-16813578|pmid-16540482|pmid-16740149|pmid-2152115|pmid-10758507|pmid-11244118|pmid-15331098|pmid-15546357|pmid-15331098|pmid-15331098|pmid-15546357|pmid-16116435
Indeed, both the intron containing and control mRNAs accumulated to 3-fold lower levels than the corresponding wild-type mRNA (35).
[ "35", "35", "36", "58" ]
131
7,931
1
false
Indeed, both the intron containing and control mRNAs accumulated to 3-fold lower levels than the corresponding wild-type mRNA.
[ "35" ]
Indeed, both the intron containing and control mRNAs accumulated to 3-fold lower levels than the corresponding wild-type mRNA.
true
true
true
true
true
1,290
4
DISCUSSION
1
36
[ "b35", "b35", "b36", "b58" ]
17,088,291
pmid-15951220|pmid-8980474|pmid-12672499|pmid-16098107|pmid-16540482|pmid-16813578|pmid-16540482|pmid-16740149|pmid-2152115|pmid-10758507|pmid-11244118|pmid-15331098|pmid-15546357|pmid-15331098|pmid-15331098|pmid-15546357|pmid-16116435
Rose has shown that incorporation of the Arabidopsis ubiquitin intron 80 nt downstream of the stop codon of the GUS reporter gene did not result in reduced reporter mRNA levels (36).
[ "35", "35", "36", "58" ]
182
7,932
1
false
Rose has shown that incorporation of the Arabidopsis ubiquitin intron 80 nt downstream of the stop codon of the GUS reporter gene did not result in reduced reporter mRNA levels.
[ "36" ]
Rose has shown that incorporation of the Arabidopsis ubiquitin intron 80 nt downstream of the stop codon of the GUS reporter gene did not result in reduced reporter mRNA levels.
true
true
true
true
true
1,290
4
DISCUSSION
1
58
[ "b35", "b35", "b36", "b58" ]
17,088,291
pmid-15951220|pmid-8980474|pmid-12672499|pmid-16098107|pmid-16540482|pmid-16813578|pmid-16540482|pmid-16740149|pmid-2152115|pmid-10758507|pmid-11244118|pmid-15331098|pmid-15546357|pmid-15331098|pmid-15331098|pmid-15546357|pmid-16116435
In mammals, different introns trigger NMD with different efficiency (58).
[ "35", "35", "36", "58" ]
73
7,933
1
false
In mammals, different introns trigger NMD with different efficiency.
[ "58" ]
In mammals, different introns trigger NMD with different efficiency.
true
true
true
true
true
1,290
4
DISCUSSION
1
35
[ "b35", "b35", "b36", "b58" ]
17,088,291
pmid-15951220|pmid-8980474|pmid-12672499|pmid-16098107|pmid-16540482|pmid-16813578|pmid-16540482|pmid-16740149|pmid-2152115|pmid-10758507|pmid-11244118|pmid-15331098|pmid-15546357|pmid-15331098|pmid-15331098|pmid-15546357|pmid-16116435
It is possible that the Ls intron triggers NMD more effectively than the ubiquitin intron.
[ "35", "35", "36", "58" ]
90
7,934
0
false
It is possible that the Ls intron triggers NMD more effectively than the ubiquitin intron.
[]
It is possible that the Ls intron triggers NMD more effectively than the ubiquitin intron.
true
true
true
true
true
1,290
4
DISCUSSION
1
35
[ "b35", "b35", "b36", "b58" ]
17,088,291
pmid-15951220|pmid-8980474|pmid-12672499|pmid-16098107|pmid-16540482|pmid-16813578|pmid-16540482|pmid-16740149|pmid-2152115|pmid-10758507|pmid-11244118|pmid-15331098|pmid-15546357|pmid-15331098|pmid-15331098|pmid-15546357|pmid-16116435
Alternatively, in plants, the intron should be more distant than 80 nt downstream of the stop codon to trigger NMD.
[ "35", "35", "36", "58" ]
115
7,935
0
false
Alternatively, in plants, the intron should be more distant than 80 nt downstream of the stop codon to trigger NMD.
[]
Alternatively, in plants, the intron should be more distant than 80 nt downstream of the stop codon to trigger NMD.
true
true
true
true
true
1,290
5
DISCUSSION
0
null
null
17,088,291
null
Identification of NMD cis elements allows the recognition of Arabidopsis genes, which could be regulated by NMD.
null
112
7,936
0
false
null
null
Identification of NMD cis elements allows the recognition of Arabidopsis genes, which could be regulated by NMD.
true
true
true
true
true
1,291
5
DISCUSSION
0
null
null
17,088,291
null
Structural targets could be transcripts with an intron in the 3′-UTR, mRNAs with long 3′-UTR, or mRNAs containing an upstream ORF (uORF) in their 5′-UTR region.
null
160
7,937
0
false
null
null
Structural targets could be transcripts with an intron in the 3′-UTR, mRNAs with long 3′-UTR, or mRNAs containing an upstream ORF (uORF) in their 5′-UTR region.
true
true
true
true
true
1,291
5
DISCUSSION
0
null
null
17,088,291
null
In silico analysis shows, that ∼30% of plant mRNAs contain uORF.
null
64
7,938
0
false
null
null
In silico analysis shows, that ∼30% of plant mRNAs contain uORF.
true
true
true
true
true
1,291
5
DISCUSSION
0
null
null
17,088,291
null
We have identified ∼1000 genes whose 3′-UTRs are longer than 500 nt and found that 3.6% of all Arabidopsis genes contain intron in their 3′-UTRs (list of genes are available as Additional Materials, ).
null
201
7,939
0
false
null
null
We have identified ∼1000 genes whose 3′-UTRs are longer than 500 nt and found that 3.6% of all Arabidopsis genes contain intron in their 3′-UTRs (list of genes are available as Additional Materials, ).
true
true
true
true
true
1,291
5
DISCUSSION
0
null
null
17,088,291
null
Therefore, it is likely that NMD also plays a role in regulation of many wild-type genes in plants.
null
99
7,940
0
false
null
null
Therefore, it is likely that NMD also plays a role in regulation of many wild-type genes in plants.
true
true
true
true
true
1,291
6
DISCUSSION
1
56
[ "b56", "b59", "b8", "b17", "b19", "b55", "b19", "b11", "b56", "b59", "b56", "b60", "b61", "b56", "b59", "b56", "b59", "b59", "b62" ]
17,088,291
pmid-16280547|pmid-12654936|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16622410|pmid-15145352|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12956953|pmid-15687506|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12654936|pmid-12654936|pmid-12468090
As the putative UPF1, 2 and 3 orthologs can be identified in each eukaryotic lineages and because the NMD system has not been found in prokaryotes, it is likely that NMD evolved in the stem eukaryotes (56,59).
[ "56", "59", "8", "17", "19", "55", "19", "11", "56", "59", "56", "60", "61", "56", "59", "56", "59", "59", "62" ]
209
7,941
0
false
As the putative UPF1, 2 and 3 orthologs can be identified in each eukaryotic lineages and because the NMD system has not been found in prokaryotes, it is likely that NMD evolved in the stem eukaryotes.
[ "56,59" ]
As the putative UPF1, 2 and 3 orthologs can be identified in each eukaryotic lineages and because the NMD system has not been found in prokaryotes, it is likely that NMD evolved in the stem eukaryotes.
true
true
true
true
true
1,292
6
DISCUSSION
1
56
[ "b56", "b59", "b8", "b17", "b19", "b55", "b19", "b11", "b56", "b59", "b56", "b60", "b61", "b56", "b59", "b56", "b59", "b59", "b62" ]
17,088,291
pmid-16280547|pmid-12654936|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16622410|pmid-15145352|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12956953|pmid-15687506|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12654936|pmid-12654936|pmid-12468090
However, the evolution of NMD system is not well understood.
[ "56", "59", "8", "17", "19", "55", "19", "11", "56", "59", "56", "60", "61", "56", "59", "56", "59", "59", "62" ]
60
7,942
0
false
However, the evolution of NMD system is not well understood.
[]
However, the evolution of NMD system is not well understood.
true
true
true
true
true
1,292
6
DISCUSSION
1
19
[ "b56", "b59", "b8", "b17", "b19", "b55", "b19", "b11", "b56", "b59", "b56", "b60", "b61", "b56", "b59", "b56", "b59", "b59", "b62" ]
17,088,291
pmid-16280547|pmid-12654936|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16622410|pmid-15145352|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12956953|pmid-15687506|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12654936|pmid-12654936|pmid-12468090
As long 3′-UTR triggers NMD in yeast, Drosophila, worm and human cells (8,17–19,55), it has been suggested that this PTC definition system is ancient (19), perhaps it was already present in the stem eukaryotes.
[ "56", "59", "8", "17", "19", "55", "19", "11", "56", "59", "56", "60", "61", "56", "59", "56", "59", "59", "62" ]
210
7,943
1
false
As long 3′-UTR triggers NMD in yeast, Drosophila, worm and human cells, it has been suggested that this PTC definition system is ancient, perhaps it was already present in the stem eukaryotes.
[ "8,17–19,55", "19" ]
As long 3′-UTR triggers NMD in yeast, Drosophila, worm and human cells, it has been suggested that this PTC definition system is ancient, perhaps it was already present in the stem eukaryotes.
true
true
true
true
true
1,292
6
DISCUSSION
1
56
[ "b56", "b59", "b8", "b17", "b19", "b55", "b19", "b11", "b56", "b59", "b56", "b60", "b61", "b56", "b59", "b56", "b59", "b59", "b62" ]
17,088,291
pmid-16280547|pmid-12654936|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16622410|pmid-15145352|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12956953|pmid-15687506|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12654936|pmid-12654936|pmid-12468090
Our result that long 3′-UTRs also trigger NMD in plants supports this hypothesis.
[ "56", "59", "8", "17", "19", "55", "19", "11", "56", "59", "56", "60", "61", "56", "59", "56", "59", "59", "62" ]
81
7,944
0
false
Our result that long 3′-UTRs also trigger NMD in plants supports this hypothesis.
[]
Our result that long 3′-UTRs also trigger NMD in plants supports this hypothesis.
true
true
true
true
true
1,292
6
DISCUSSION
1
56
[ "b56", "b59", "b8", "b17", "b19", "b55", "b19", "b11", "b56", "b59", "b56", "b60", "b61", "b56", "b59", "b56", "b59", "b59", "b62" ]
17,088,291
pmid-16280547|pmid-12654936|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16622410|pmid-15145352|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12956953|pmid-15687506|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12654936|pmid-12654936|pmid-12468090
The evolution of intron-based PTC definition is more debated.
[ "56", "59", "8", "17", "19", "55", "19", "11", "56", "59", "56", "60", "61", "56", "59", "56", "59", "59", "62" ]
61
7,945
0
false
The evolution of intron-based PTC definition is more debated.
[]
The evolution of intron-based PTC definition is more debated.
true
true
true
true
true
1,292
6
DISCUSSION
1
11
[ "b56", "b59", "b8", "b17", "b19", "b55", "b19", "b11", "b56", "b59", "b56", "b60", "b61", "b56", "b59", "b56", "b59", "b59", "b62" ]
17,088,291
pmid-16280547|pmid-12654936|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16622410|pmid-15145352|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12956953|pmid-15687506|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12654936|pmid-12654936|pmid-12468090
Based on the findings that introns are not NMD cis elements in yeast or Drosophila, it has been suggested that the intron-based PTC definition evolved late, only when alternative splicing had become dominant in certain animal lineages (11).
[ "56", "59", "8", "17", "19", "55", "19", "11", "56", "59", "56", "60", "61", "56", "59", "56", "59", "59", "62" ]
240
7,946
1
false
Based on the findings that introns are not NMD cis elements in yeast or Drosophila, it has been suggested that the intron-based PTC definition evolved late, only when alternative splicing had become dominant in certain animal lineages.
[ "11" ]
Based on the findings that introns are not NMD cis elements in yeast or Drosophila, it has been suggested that the intron-based PTC definition evolved late, only when alternative splicing had become dominant in certain animal lineages.
true
true
true
true
true
1,292
6
DISCUSSION
1
56
[ "b56", "b59", "b8", "b17", "b19", "b55", "b19", "b11", "b56", "b59", "b56", "b60", "b61", "b56", "b59", "b56", "b59", "b59", "b62" ]
17,088,291
pmid-16280547|pmid-12654936|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16622410|pmid-15145352|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12956953|pmid-15687506|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12654936|pmid-12654936|pmid-12468090
An alternative model of NMD evolution has proposed that the intron-based PTC definition has already operated in the stem eukaryotes.
[ "56", "59", "8", "17", "19", "55", "19", "11", "56", "59", "56", "60", "61", "56", "59", "56", "59", "59", "62" ]
132
7,947
0
false
An alternative model of NMD evolution has proposed that the intron-based PTC definition has already operated in the stem eukaryotes.
[]
An alternative model of NMD evolution has proposed that the intron-based PTC definition has already operated in the stem eukaryotes.
true
true
true
true
true
1,292
6
DISCUSSION
1
56
[ "b56", "b59", "b8", "b17", "b19", "b55", "b19", "b11", "b56", "b59", "b56", "b60", "b61", "b56", "b59", "b56", "b59", "b59", "b62" ]
17,088,291
pmid-16280547|pmid-12654936|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16622410|pmid-15145352|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12956953|pmid-15687506|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12654936|pmid-12654936|pmid-12468090
This model suggests that splicing and NMD were coupled by the EJC in these ancient organisms (56,59).
[ "56", "59", "8", "17", "19", "55", "19", "11", "56", "59", "56", "60", "61", "56", "59", "56", "59", "59", "62" ]
101
7,948
0
false
This model suggests that splicing and NMD were coupled by the EJC in these ancient organisms.
[ "56,59" ]
This model suggests that splicing and NMD were coupled by the EJC in these ancient organisms.
true
true
true
true
true
1,292
6
DISCUSSION
1
56
[ "b56", "b59", "b8", "b17", "b19", "b55", "b19", "b11", "b56", "b59", "b56", "b60", "b61", "b56", "b59", "b56", "b59", "b59", "b62" ]
17,088,291
pmid-16280547|pmid-12654936|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16622410|pmid-15145352|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12956953|pmid-15687506|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12654936|pmid-12654936|pmid-12468090
As the EJC components (56) and many introns (60,61) are highly conserved in eukaryotes, this model hypothesizes that in stem eukaryotes EJC-based NMD could efficiently eliminate PTC-containing mRNAs of spliced transcripts, thereby providing primary positive selection for the intron containing alleles.
[ "56", "59", "8", "17", "19", "55", "19", "11", "56", "59", "56", "60", "61", "56", "59", "56", "59", "59", "62" ]
302
7,949
1
false
As the EJC components and many introns are highly conserved in eukaryotes, this model hypothesizes that in stem eukaryotes EJC-based NMD could efficiently eliminate PTC-containing mRNAs of spliced transcripts, thereby providing primary positive selection for the intron containing alleles.
[ "56", "60,61" ]
As the EJC components and many introns are highly conserved in eukaryotes, this model hypothesizes that in stem eukaryotes EJC-based NMD could efficiently eliminate PTC-containing mRNAs of spliced transcripts, thereby providing primary positive selection for the intron containing alleles.
true
true
true
true
true
1,292
6
DISCUSSION
1
56
[ "b56", "b59", "b8", "b17", "b19", "b55", "b19", "b11", "b56", "b59", "b56", "b60", "b61", "b56", "b59", "b56", "b59", "b59", "b62" ]
17,088,291
pmid-16280547|pmid-12654936|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16622410|pmid-15145352|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12956953|pmid-15687506|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12654936|pmid-12654936|pmid-12468090
Consequently, NMD facilitated the rapid spreading of ancient introns in stem eukaryotes (56,59).
[ "56", "59", "8", "17", "19", "55", "19", "11", "56", "59", "56", "60", "61", "56", "59", "56", "59", "59", "62" ]
96
7,950
0
false
Consequently, NMD facilitated the rapid spreading of ancient introns in stem eukaryotes.
[ "56,59" ]
Consequently, NMD facilitated the rapid spreading of ancient introns in stem eukaryotes.
true
true
true
true
true
1,292
6
DISCUSSION
1
56
[ "b56", "b59", "b8", "b17", "b19", "b55", "b19", "b11", "b56", "b59", "b56", "b60", "b61", "b56", "b59", "b56", "b59", "b59", "b62" ]
17,088,291
pmid-16280547|pmid-12654936|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16622410|pmid-15145352|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12956953|pmid-15687506|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12654936|pmid-12654936|pmid-12468090
The finding that 3′-UTR located introns trigger NMD in a position-dependent manner in plants is consistent with this model.
[ "56", "59", "8", "17", "19", "55", "19", "11", "56", "59", "56", "60", "61", "56", "59", "56", "59", "59", "62" ]
123
7,951
0
false
The finding that 3′-UTR located introns trigger NMD in a position-dependent manner in plants is consistent with this model.
[]
The finding that 3′-UTR located introns trigger NMD in a position-dependent manner in plants is consistent with this model.
true
true
true
true
true
1,292
6
DISCUSSION
1
56
[ "b56", "b59", "b8", "b17", "b19", "b55", "b19", "b11", "b56", "b59", "b56", "b60", "b61", "b56", "b59", "b56", "b59", "b59", "b62" ]
17,088,291
pmid-16280547|pmid-12654936|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16622410|pmid-15145352|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12956953|pmid-15687506|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12654936|pmid-12654936|pmid-12468090
This model also predicts that introns should be ∼evenly distributed within the coding regions (56,59).
[ "56", "59", "8", "17", "19", "55", "19", "11", "56", "59", "56", "60", "61", "56", "59", "56", "59", "59", "62" ]
102
7,952
0
false
This model also predicts that introns should be ∼evenly distributed within the coding regions.
[ "56,59" ]
This model also predicts that introns should be ∼evenly distributed within the coding regions.
true
true
true
true
true
1,292
6
DISCUSSION
1
56
[ "b56", "b59", "b8", "b17", "b19", "b55", "b19", "b11", "b56", "b59", "b56", "b60", "b61", "b56", "b59", "b56", "b59", "b59", "b62" ]
17,088,291
pmid-16280547|pmid-12654936|pmid-15525991|pmid-12881430|pmid-16622410|pmid-11672865|pmid-16622410|pmid-15145352|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12956953|pmid-15687506|pmid-16280547|pmid-12654936|pmid-16280547|pmid-12654936|pmid-12654936|pmid-12468090
Indeed, we and others (59,62) have shown that plant introns are distributed relatively equally along the coding regions except the very 5′ and 3′ regions (Additional Materials).
[ "56", "59", "8", "17", "19", "55", "19", "11", "56", "59", "56", "60", "61", "56", "59", "56", "59", "59", "62" ]
177
7,953
0
false
Indeed, we and others have shown that plant introns are distributed relatively equally along the coding regions except the very 5′ and 3′ regions (Additional Materials).
[ "59,62" ]
Indeed, we and others have shown that plant introns are distributed relatively equally along the coding regions except the very 5′ and 3′ regions (Additional Materials).
true
true
true
true
true
1,292
7
DISCUSSION
0
null
null
17,088,291
null
Taken together, our findings suggest that both long 3′-UTR and intron-based PTC definition systems could operate in stem eukaryotes.
null
132
7,954
0
false
null
null
Taken together, our findings suggest that both long 3′-UTR and intron-based PTC definition systems could operate in stem eukaryotes.
true
true
true
true
true
1,293
7
DISCUSSION
0
null
null
17,088,291
null
In lineages, in which intron loss dominated (yeast, Drosophila etc.
null
67
7,955
0
false
null
null
In lineages, in which intron loss dominated (yeast, Drosophila etc.
true
true
true
true
true
1,293
7
DISCUSSION
0
null
null
17,088,291
null
), splicing and NMD could be evolutionarily uncoupled, thus long 3′-UTR became the dominant NMD cis element.
null
108
7,956
0
false
null
null
), splicing and NMD could be evolutionarily uncoupled, thus long 3′-UTR became the dominant NMD cis element.
false
false
true
true
false
1,293
7
DISCUSSION
0
null
null
17,088,291
null
In contrast, in the extremely intron-dense lineages, where alternative splicing is very widely used (mammals), introns could become the more efficient and dominating NMD cis elements.
null
183
7,957
0
false
null
null
In contrast, in the extremely intron-dense lineages, where alternative splicing is very widely used (mammals), introns could become the more efficient and dominating NMD cis elements.
true
true
true
true
true
1,293
7
DISCUSSION
0
null
null
17,088,291
null
Although, plants are intron-dense organisms, intronless genes are also frequently found in the plant genome, thus NMD machinery has evolved under dual constrains, it should efficiently identify PTC-containing mRNAs derived from either intronless or intron containing genes.
null
273
7,958
0
false
null
null
Although, plants are intron-dense organisms, intronless genes are also frequently found in the plant genome, thus NMD machinery has evolved under dual constrains, it should efficiently identify PTC-containing mRNAs derived from either intronless or intron containing genes.
true
true
true
true
true
1,293
7
DISCUSSION
0
null
null
17,088,291
null
Therefore, both long 3′-UTR and intron-based PTC recognition machinery should work efficiently in plants.
null
105
7,959
0
false
null
null
Therefore, both long 3′-UTR and intron-based PTC recognition machinery should work efficiently in plants.
true
true
true
true
true
1,293
0
INTRODUCTION
1
1
[ "b1", "b9", "b4", "b7", "b10", "b8", "b11" ]
17,175,534
pmid-9421513|pmid-12060689|pmid-10556321|pmid-12783628|pmid-16314312|pmid-9461475|pmid-15070404
Since the mid-1990s, automated gene finders for prokaryotic genome sequences have become available that allow the unsupervised discovery of genes from raw genomic sequence (1–9).
[ "1", "9", "4", "7", "10", "8", "11" ]
178
7,960
0
false
Since the mid-1990s, automated gene finders for prokaryotic genome sequences have become available that allow the unsupervised discovery of genes from raw genomic sequence.
[ "1–9" ]
Since the mid-1990s, automated gene finders for prokaryotic genome sequences have become available that allow the unsupervised discovery of genes from raw genomic sequence.
true
true
true
true
true
1,294
0
INTRODUCTION
1
1
[ "b1", "b9", "b4", "b7", "b10", "b8", "b11" ]
17,175,534
pmid-9421513|pmid-12060689|pmid-10556321|pmid-12783628|pmid-16314312|pmid-9461475|pmid-15070404
This accomplishment, accompanied by impressive values of accuracy, has made prokaryotic gene prediction one of the showcases of computational biology.
[ "1", "9", "4", "7", "10", "8", "11" ]
150
7,961
0
false
This accomplishment, accompanied by impressive values of accuracy, has made prokaryotic gene prediction one of the showcases of computational biology.
[]
This accomplishment, accompanied by impressive values of accuracy, has made prokaryotic gene prediction one of the showcases of computational biology.
true
true
true
true
true
1,294
0
INTRODUCTION
1
4
[ "b1", "b9", "b4", "b7", "b10", "b8", "b11" ]
17,175,534
pmid-9421513|pmid-12060689|pmid-10556321|pmid-12783628|pmid-16314312|pmid-9461475|pmid-15070404
Subsequent developments have focused mostly on the introduction of novel techniques to more accurately capture sequence composition (4), modeling of the gene structure (7,10) and development of models that allow the unsupervised discovery of multiple gene classes (8,11).
[ "1", "9", "4", "7", "10", "8", "11" ]
271
7,962
1
false
Subsequent developments have focused mostly on the introduction of novel techniques to more accurately capture sequence composition, modeling of the gene structure and development of models that allow the unsupervised discovery of multiple gene classes.
[ "4", "7,10", "8,11" ]
Subsequent developments have focused mostly on the introduction of novel techniques to more accurately capture sequence composition, modeling of the gene structure and development of models that allow the unsupervised discovery of multiple gene classes.
true
true
true
true
true
1,294
1
INTRODUCTION
1
6
[ "b6", "b12", "b13" ]
17,175,534
pmid-12626720|pmid-14988122|pmid-14965344
Because of the high accuracy initially reported for most programs, some might consider prokaryotic gene prediction solved, but from the point of a practitioner, this is not quite the case yet.
[ "6", "12", "13" ]
192
7,963
0
false
Because of the high accuracy initially reported for most programs, some might consider prokaryotic gene prediction solved, but from the point of a practitioner, this is not quite the case yet.
[]
Because of the high accuracy initially reported for most programs, some might consider prokaryotic gene prediction solved, but from the point of a practitioner, this is not quite the case yet.
true
true
true
true
true
1,295
1
INTRODUCTION
1
6
[ "b6", "b12", "b13" ]
17,175,534
pmid-12626720|pmid-14988122|pmid-14965344
For some programs the predictive accuracy is uncertain, as they have not been re-evaluated since the original evaluation on a handful of genomes.
[ "6", "12", "13" ]
145
7,964
0
false
For some programs the predictive accuracy is uncertain, as they have not been re-evaluated since the original evaluation on a handful of genomes.
[]
For some programs the predictive accuracy is uncertain, as they have not been re-evaluated since the original evaluation on a handful of genomes.
true
true
true
true
true
1,295
1
INTRODUCTION
1
6
[ "b6", "b12", "b13" ]
17,175,534
pmid-12626720|pmid-14988122|pmid-14965344
The recent development of techniques that improve predictions by combining the output of multiple programs (6,12,13) shows that accuracy can be increased.
[ "6", "12", "13" ]
154
7,965
0
false
The recent development of techniques that improve predictions by combining the output of multiple programs shows that accuracy can be increased.
[ "6,12,13" ]
The recent development of techniques that improve predictions by combining the output of multiple programs shows that accuracy can be increased.
true
true
true
true
true
1,295
1
INTRODUCTION
1
6
[ "b6", "b12", "b13" ]
17,175,534
pmid-12626720|pmid-14988122|pmid-14965344
Another issue is that some programs are only accessible via a web interface, which for genome projects—due to the confidentiality of the data—is frequently not an option.
[ "6", "12", "13" ]
170
7,966
0
false
Another issue is that some programs are only accessible via a web interface, which for genome projects—due to the confidentiality of the data—is frequently not an option.
[]
Another issue is that some programs are only accessible via a web interface, which for genome projects—due to the confidentiality of the data—is frequently not an option.
true
true
true
true
true
1,295
2
INTRODUCTION
1
14
[ "b14", "b15", "b16", "b17", "b19", "b20", "b21", "b22", "b24" ]
17,175,534
pmid-9837738|NA|NA|pmid-14630658|pmid-11928508|pmid-12758155|pmid-10618406|pmid-10075995|pmid-10508724
Here we describe our novel gene finder GISMO (Gene Identification using a Support Vector Machine for ORF classification), which is freely available under the GPL license.
[ "14", "15", "16", "17", "19", "20", "21", "22", "24" ]
170
7,967
0
false
Here we describe our novel gene finder GISMO (Gene Identification using a Support Vector Machine for ORF classification), which is freely available under the GPL license.
[]
Here we describe our novel gene finder GISMO (Gene Identification using a Support Vector Machine for ORF classification), which is freely available under the GPL license.
true
true
true
true
true
1,296
2
INTRODUCTION
1
14
[ "b14", "b15", "b16", "b17", "b19", "b20", "b21", "b22", "b24" ]
17,175,534
pmid-9837738|NA|NA|pmid-14630658|pmid-11928508|pmid-12758155|pmid-10618406|pmid-10075995|pmid-10508724
GISMO has high classification accuracy: it is very sensitive, meaning that it identifies most known genes, and specific, i.e.
[ "14", "15", "16", "17", "19", "20", "21", "22", "24" ]
125
7,968
0
false
GISMO has high classification accuracy: it is very sensitive, meaning that it identifies most known genes, and specific, i.e.
[]
GISMO has high classification accuracy: it is very sensitive, meaning that it identifies most known genes, and specific, i.e.
true
true
true
true
true
1,296
2
INTRODUCTION
1
14
[ "b14", "b15", "b16", "b17", "b19", "b20", "b21", "b22", "b24" ]
17,175,534
pmid-9837738|NA|NA|pmid-14630658|pmid-11928508|pmid-12758155|pmid-10618406|pmid-10075995|pmid-10508724
it produces reliable predictions.
[ "14", "15", "16", "17", "19", "20", "21", "22", "24" ]
33
7,969
0
false
it produces reliable predictions.
[]
it produces reliable predictions.
false
true
true
true
false
1,296
2
INTRODUCTION
1
14
[ "b14", "b15", "b16", "b17", "b19", "b20", "b21", "b22", "b24" ]
17,175,534
pmid-9837738|NA|NA|pmid-14630658|pmid-11928508|pmid-12758155|pmid-10618406|pmid-10075995|pmid-10508724
Our program combines a hidden Markov model (HMM)-based search for protein domains with a support vector machine (SVM) to identify coding regions based on sequence composition.
[ "14", "15", "16", "17", "19", "20", "21", "22", "24" ]
175
7,970
0
false
Our program combines a hidden Markov model (HMM)-based search for protein domains with a support vector machine (SVM) to identify coding regions based on sequence composition.
[]
Our program combines a hidden Markov model (HMM)-based search for protein domains with a support vector machine (SVM) to identify coding regions based on sequence composition.
true
true
true
true
true
1,296
2
INTRODUCTION
1
14
[ "b14", "b15", "b16", "b17", "b19", "b20", "b21", "b22", "b24" ]
17,175,534
pmid-9837738|NA|NA|pmid-14630658|pmid-11928508|pmid-12758155|pmid-10618406|pmid-10075995|pmid-10508724
An advantage of the HMM-based search for protein domains compared with pair-wise sequence searches is the higher accuracy in discriminating between signal and noise for protein family members (14).
[ "14", "15", "16", "17", "19", "20", "21", "22", "24" ]
197
7,971
1
false
An advantage of the HMM-based search for protein domains compared with pair-wise sequence searches is the higher accuracy in discriminating between signal and noise for protein family members.
[ "14" ]
An advantage of the HMM-based search for protein domains compared with pair-wise sequence searches is the higher accuracy in discriminating between signal and noise for protein family members.
true
true
true
true
true
1,296
2
INTRODUCTION
1
14
[ "b14", "b15", "b16", "b17", "b19", "b20", "b21", "b22", "b24" ]
17,175,534
pmid-9837738|NA|NA|pmid-14630658|pmid-11928508|pmid-12758155|pmid-10618406|pmid-10075995|pmid-10508724
Also, genes with new orderings of known protein domains can be detected easily.
[ "14", "15", "16", "17", "19", "20", "21", "22", "24" ]
79
7,972
0
false
Also, genes with new orderings of known protein domains can be detected easily.
[]
Also, genes with new orderings of known protein domains can be detected easily.
true
true
true
true
true
1,296
2
INTRODUCTION
1
14
[ "b14", "b15", "b16", "b17", "b19", "b20", "b21", "b22", "b24" ]
17,175,534
pmid-9837738|NA|NA|pmid-14630658|pmid-11928508|pmid-12758155|pmid-10618406|pmid-10075995|pmid-10508724
An SVM classifier is constructed for composition-based identification of protein-encoding genes.
[ "14", "15", "16", "17", "19", "20", "21", "22", "24" ]
96
7,973
0
false
An SVM classifier is constructed for composition-based identification of protein-encoding genes.
[]
An SVM classifier is constructed for composition-based identification of protein-encoding genes.
true
true
true
true
true
1,296
2
INTRODUCTION
1
20
[ "b14", "b15", "b16", "b17", "b19", "b20", "b21", "b22", "b24" ]
17,175,534
pmid-9837738|NA|NA|pmid-14630658|pmid-11928508|pmid-12758155|pmid-10618406|pmid-10075995|pmid-10508724
The SVM is a machine learning technique with a strong theoretical foundation (15,16) that has been used to improve classification accuracy in biological applications such as the detection of protein family members (17–19), RNA and DNA binding proteins (20), and the functional classification of gene expression data (21)...
[ "14", "15", "16", "17", "19", "20", "21", "22", "24" ]
321
7,974
1
false
The SVM is a machine learning technique with a strong theoretical foundation that has been used to improve classification accuracy in biological applications such as the detection of protein family members, RNA and DNA binding proteins, and the functional classification of gene expression data.
[ "15,16", "17–19", "20", "21" ]
The SVM is a machine learning technique with a strong theoretical foundation that has been used to improve classification accuracy in biological applications such as the detection of protein family members, RNA and DNA binding proteins, and the functional classification of gene expression data.
true
true
true
true
true
1,296
2
INTRODUCTION
1
14
[ "b14", "b15", "b16", "b17", "b19", "b20", "b21", "b22", "b24" ]
17,175,534
pmid-9837738|NA|NA|pmid-14630658|pmid-11928508|pmid-12758155|pmid-10618406|pmid-10075995|pmid-10508724
The SVM is a maximum margin classifier that can solve non-linear classification problems by learning an optimally separating hyperplane in a higher-dimensional feature space.
[ "14", "15", "16", "17", "19", "20", "21", "22", "24" ]
174
7,975
0
false
The SVM is a maximum margin classifier that can solve non-linear classification problems by learning an optimally separating hyperplane in a higher-dimensional feature space.
[]
The SVM is a maximum margin classifier that can solve non-linear classification problems by learning an optimally separating hyperplane in a higher-dimensional feature space.
true
true
true
true
true
1,296
2
INTRODUCTION
1
14
[ "b14", "b15", "b16", "b17", "b19", "b20", "b21", "b22", "b24" ]
17,175,534
pmid-9837738|NA|NA|pmid-14630658|pmid-11928508|pmid-12758155|pmid-10618406|pmid-10075995|pmid-10508724
By use of non-linear kernel functions such as a Gaussian kernel, complex and non-linear decision functions can be learned by the SVM.
[ "14", "15", "16", "17", "19", "20", "21", "22", "24" ]
133
7,976
0
false
By use of non-linear kernel functions such as a Gaussian kernel, complex and non-linear decision functions can be learned by the SVM.
[]
By use of non-linear kernel functions such as a Gaussian kernel, complex and non-linear decision functions can be learned by the SVM.
true
true
true
true
true
1,296
2
INTRODUCTION
1
14
[ "b14", "b15", "b16", "b17", "b19", "b20", "b21", "b22", "b24" ]
17,175,534
pmid-9837738|NA|NA|pmid-14630658|pmid-11928508|pmid-12758155|pmid-10618406|pmid-10075995|pmid-10508724
Even if items of one class are clustered in multiple separate sub-regions in the input space they can be clearly separated from the other class (Figure 1).
[ "14", "15", "16", "17", "19", "20", "21", "22", "24" ]
155
7,977
0
false
Even if items of one class are clustered in multiple separate sub-regions in the input space they can be clearly separated from the other class (Figure 1).
[]
Even if items of one class are clustered in multiple separate sub-regions in the input space they can be clearly separated from the other class.
true
true
true
true
true
1,296
2
INTRODUCTION
1
14
[ "b14", "b15", "b16", "b17", "b19", "b20", "b21", "b22", "b24" ]
17,175,534
pmid-9837738|NA|NA|pmid-14630658|pmid-11928508|pmid-12758155|pmid-10618406|pmid-10075995|pmid-10508724
The learnt hyperplane allows accurate discrimination between classes that cannot be separated linearly in the input space, as may be the case when phenomena such as horizontal gene transfer, translational selection and leading/lagging strand biases influence the sequence composition of genes (22–24).
[ "14", "15", "16", "17", "19", "20", "21", "22", "24" ]
301
7,978
0
false
The learnt hyperplane allows accurate discrimination between classes that cannot be separated linearly in the input space, as may be the case when phenomena such as horizontal gene transfer, translational selection and leading/lagging strand biases influence the sequence composition of genes.
[ "22–24" ]
The learnt hyperplane allows accurate discrimination between classes that cannot be separated linearly in the input space, as may be the case when phenomena such as horizontal gene transfer, translational selection and leading/lagging strand biases influence the sequence composition of genes.
true
true
true
true
true
1,296
3
INTRODUCTION
1
30
[ "b30" ]
17,175,534
NA
Class boundaries learned by the SVM with different kernel functions.
[ "30" ]
68
7,979
0
false
Class boundaries learned by the SVM with different kernel functions.
[]
Class boundaries learned by the SVM with different kernel functions.
true
true
true
true
true
1,297
3
INTRODUCTION
1
30
[ "b30" ]
17,175,534
NA
Circles and crosses represent instances of a toy example training set.
[ "30" ]
70
7,980
0
false
Circles and crosses represent instances of a toy example training set.
[]
Circles and crosses represent instances of a toy example training set.
true
true
true
true
true
1,297
3
INTRODUCTION
1
30
[ "b30" ]
17,175,534
NA
Colored regions indicate the two classes learned by three example SVM applications.
[ "30" ]
83
7,981
0
false
Colored regions indicate the two classes learned by three example SVM applications.
[]
Colored regions indicate the two classes learned by three example SVM applications.
true
true
true
true
true
1,297
3
INTRODUCTION
1
30
[ "b30" ]
17,175,534
NA
(A) A linear decision function learned with a linear kernel.
[ "30" ]
60
7,982
0
false
(A) A linear decision function learned with a linear kernel.
[]
(A) A linear decision function learned with a linear kernel.
false
false
true
true
false
1,297
3
INTRODUCTION
1
30
[ "b30" ]
17,175,534
NA
(B) A polynomial kernel allows realization of a polynomial separating surface.
[ "30" ]
78
7,983
0
false
(B) A polynomial kernel allows realization of a polynomial separating surface.
[]
(B) A polynomial kernel allows realization of a polynomial separating surface.
false
false
true
true
false
1,297
3
INTRODUCTION
1
30
[ "b30" ]
17,175,534
NA
(C) With a Gaussian kernel the SVM can learn disjoint decision functions that surround a multitude of ‘islands’ of items from the same class (30).
[ "30" ]
146
7,984
1
false
(C) With a Gaussian kernel the SVM can learn disjoint decision functions that surround a multitude of ‘islands’ of items from the same class.
[ "30" ]
(C) With a Gaussian kernel the SVM can learn disjoint decision functions that surround a multitude of ‘islands’ of items from the same class.
false
false
true
true
false
1,297
4
INTRODUCTION
1
7
[ "b7", "b25" ]
17,175,534
pmid-12783628|pmid-16922601
GISMO was evaluated with 165 prokaryotic chromosomes and 223 plasmid sequences.
[ "7", "25" ]
79
7,985
0
false
GISMO was evaluated with 165 prokaryotic chromosomes and 223 plasmid sequences.
[]
GISMO was evaluated with 165 prokaryotic chromosomes and 223 plasmid sequences.
true
true
true
true
true
1,298
4
INTRODUCTION
1
7
[ "b7", "b25" ]
17,175,534
pmid-12783628|pmid-16922601
For the chromosomal sequences, GISMO identified 94.3% of the genes (98.9% for genes with annotated function), and 94.3% of its predictions corresponded to annotated genes.
[ "7", "25" ]
171
7,986
0
false
For the chromosomal sequences, GISMO identified 94.3% of the genes (98.9% for genes with annotated function), and 94.3% of its predictions corresponded to annotated genes.
[]
For the chromosomal sequences, GISMO identified 94.3% of the genes (98.9% for genes with annotated function), and 94.3% of its predictions corresponded to annotated genes.
true
true
true
true
true
1,298
4
INTRODUCTION
1
7
[ "b7", "b25" ]
17,175,534
pmid-12783628|pmid-16922601
Several thousand of the new predictions for the published genomes are supported by extrinsic evidence, suggesting that these very probably are biologically active genes that are missing in the annotations.
[ "7", "25" ]
205
7,987
0
false
Several thousand of the new predictions for the published genomes are supported by extrinsic evidence, suggesting that these very probably are biologically active genes that are missing in the annotations.
[]
Several thousand of the new predictions for the published genomes are supported by extrinsic evidence, suggesting that these very probably are biologically active genes that are missing in the annotations.
true
true
true
true
true
1,298
4
INTRODUCTION
1
7
[ "b7", "b25" ]
17,175,534
pmid-12783628|pmid-16922601
We also address some of the most challenging problems for prokaryotic gene finders, including the correct identification of short genes (7,25) and of genes with atypical sequence composition and the prediction of genes when only little sequence material is available, as in the case of extrachromosomal replicons.
[ "7", "25" ]
313
7,988
0
false
We also address some of the most challenging problems for prokaryotic gene finders, including the correct identification of short genes and of genes with atypical sequence composition and the prediction of genes when only little sequence material is available, as in the case of extrachromosomal replicons.
[ "7,25" ]
We also address some of the most challenging problems for prokaryotic gene finders, including the correct identification of short genes and of genes with atypical sequence composition and the prediction of genes when only little sequence material is available, as in the case of extrachromosomal replicons.
true
true
true
true
true
1,298
4
INTRODUCTION
1
7
[ "b7", "b25" ]
17,175,534
pmid-12783628|pmid-16922601
The composition-based SVM, which uses vectors of sequence composition in the (low-dimensional) space of codon usage, is well suited for these tasks and achieved the highest classification accuracy for all cases when compared with two other popular, freely available programs.
[ "7", "25" ]
275
7,989
0
false
The composition-based SVM, which uses vectors of sequence composition in the (low-dimensional) space of codon usage, is well suited for these tasks and achieved the highest classification accuracy for all cases when compared with two other popular, freely available programs.
[]
The composition-based SVM, which uses vectors of sequence composition in the (low-dimensional) space of codon usage, is well suited for these tasks and achieved the highest classification accuracy for all cases when compared with two other popular, freely available programs.
true
true
true
true
true
1,298
4
INTRODUCTION
1
7
[ "b7", "b25" ]
17,175,534
pmid-12783628|pmid-16922601
GISMO predictions for the 165 genomic sequences are available for download in GFF at .
[ "7", "25" ]
86
7,990
0
false
GISMO predictions for the 165 genomic sequences are available for download in GFF at.
[]
GISMO predictions for the 165 genomic sequences are available for download in GFF at.
true
true
true
true
true
1,298
0
INTRODUCTION
1
1–3
[ "B1 B2 B3", "B4", "B5", "B6", "B7", "B8", "B9", "B10", "B11", "B4", "B12 B13 B14 B15 B16" ]
17,395,637
pmid-16959964|pmid-16885020|pmid-16720337|pmid-9334325|pmid-12706900|pmid-9593731|pmid-10574912|pmid-8900211|pmid-7759473|pmid-9450929|pmid-16427012|pmid-9334325|pmid-9334326|pmid-9649438|pmid-10384302|pmid-9491887|pmid-11545735
P-TEFb plays a key role in RNA polymerase II elongation control (1–3).
[ "1–3", "4", "5", "6", "7", "8", "9", "10", "11", "4", "12–16" ]
70
7,991
1
false
P-TEFb plays a key role in RNA polymerase II elongation control.
[ "1–3" ]
P-TEFb plays a key role in RNA polymerase II elongation control.
true
true
true
true
true
1,299
0
INTRODUCTION
1
6
[ "B1 B2 B3", "B4", "B5", "B6", "B7", "B8", "B9", "B10", "B11", "B4", "B12 B13 B14 B15 B16" ]
17,395,637
pmid-16959964|pmid-16885020|pmid-16720337|pmid-9334325|pmid-12706900|pmid-9593731|pmid-10574912|pmid-8900211|pmid-7759473|pmid-9450929|pmid-16427012|pmid-9334325|pmid-9334326|pmid-9649438|pmid-10384302|pmid-9491887|pmid-11545735
It is comprised of one of two isoforms of Cdk9 (4,5) and one of three cyclins, T1, T2 (6) or K (7) in humans.
[ "1–3", "4", "5", "6", "7", "8", "9", "10", "11", "4", "12–16" ]
109
7,992
1
false
It is comprised of one of two isoforms of Cdk9 and one of three cyclins, T1, T2 or K in humans.
[ "4,5", "6", "7" ]
It is comprised of one of two isoforms of Cdk9 and one of three cyclins, T1, T2 or K in humans.
true
true
true
true
true
1,299
0
INTRODUCTION
1
8
[ "B1 B2 B3", "B4", "B5", "B6", "B7", "B8", "B9", "B10", "B11", "B4", "B12 B13 B14 B15 B16" ]
17,395,637
pmid-16959964|pmid-16885020|pmid-16720337|pmid-9334325|pmid-12706900|pmid-9593731|pmid-10574912|pmid-8900211|pmid-7759473|pmid-9450929|pmid-16427012|pmid-9334325|pmid-9334326|pmid-9649438|pmid-10384302|pmid-9491887|pmid-11545735
One of the major targets of the kinase activity of P-TEFb is the carboxyl-terminal domain (CTD) of the largest subunit of RNA polymerase II (8), and this phosphorylation of the CTD by P-TEFb occurs during transcription elongation (9).
[ "1–3", "4", "5", "6", "7", "8", "9", "10", "11", "4", "12–16" ]
234
7,993
1
false
One of the major targets of the kinase activity of P-TEFb is the carboxyl-terminal domain (CTD) of the largest subunit of RNA polymerase II, and this phosphorylation of the CTD by P-TEFb occurs during transcription elongation.
[ "8", "9" ]
One of the major targets of the kinase activity of P-TEFb is the carboxyl-terminal domain (CTD) of the largest subunit of RNA polymerase II, and this phosphorylation of the CTD by P-TEFb occurs during transcription elongation.
true
true
true
true
true
1,299
0
INTRODUCTION
1
10
[ "B1 B2 B3", "B4", "B5", "B6", "B7", "B8", "B9", "B10", "B11", "B4", "B12 B13 B14 B15 B16" ]
17,395,637
pmid-16959964|pmid-16885020|pmid-16720337|pmid-9334325|pmid-12706900|pmid-9593731|pmid-10574912|pmid-8900211|pmid-7759473|pmid-9450929|pmid-16427012|pmid-9334325|pmid-9334326|pmid-9649438|pmid-10384302|pmid-9491887|pmid-11545735
P-TEFb also phosphorylates the negative transcription elongation factor DSIF (10), turning it into a positive elongation factor (11).
[ "1–3", "4", "5", "6", "7", "8", "9", "10", "11", "4", "12–16" ]
133
7,994
1
false
P-TEFb also phosphorylates the negative transcription elongation factor DSIF, turning it into a positive elongation factor.
[ "10", "11" ]
P-TEFb also phosphorylates the negative transcription elongation factor DSIF, turning it into a positive elongation factor.
true
true
true
true
true
1,299
0
INTRODUCTION
1
1–3
[ "B1 B2 B3", "B4", "B5", "B6", "B7", "B8", "B9", "B10", "B11", "B4", "B12 B13 B14 B15 B16" ]
17,395,637
pmid-16959964|pmid-16885020|pmid-16720337|pmid-9334325|pmid-12706900|pmid-9593731|pmid-10574912|pmid-8900211|pmid-7759473|pmid-9450929|pmid-16427012|pmid-9334325|pmid-9334326|pmid-9649438|pmid-10384302|pmid-9491887|pmid-11545735
P-TEFb controls gene expression by regulating the fraction of RNA polymerase II molecules that generate full-length mRNAs.
[ "1–3", "4", "5", "6", "7", "8", "9", "10", "11", "4", "12–16" ]
122
7,995
0
false
P-TEFb controls gene expression by regulating the fraction of RNA polymerase II molecules that generate full-length mRNAs.
[]
P-TEFb controls gene expression by regulating the fraction of RNA polymerase II molecules that generate full-length mRNAs.
true
true
true
true
true
1,299
0
INTRODUCTION
1
1–3
[ "B1 B2 B3", "B4", "B5", "B6", "B7", "B8", "B9", "B10", "B11", "B4", "B12 B13 B14 B15 B16" ]
17,395,637
pmid-16959964|pmid-16885020|pmid-16720337|pmid-9334325|pmid-12706900|pmid-9593731|pmid-10574912|pmid-8900211|pmid-7759473|pmid-9450929|pmid-16427012|pmid-9334325|pmid-9334326|pmid-9649438|pmid-10384302|pmid-9491887|pmid-11545735
In addition to its normal cellular role, P-TEFb has been shown to be recruited by viral transactivator Tat to the nascent viral transcript, TAR, near the promoter to enhance viral transcription, which is required for efficient HIV-1 replication (4,12–16).
[ "1–3", "4", "5", "6", "7", "8", "9", "10", "11", "4", "12–16" ]
255
7,996
0
false
In addition to its normal cellular role, P-TEFb has been shown to be recruited by viral transactivator Tat to the nascent viral transcript, TAR, near the promoter to enhance viral transcription, which is required for efficient HIV-1 replication.
[ "4,12–16" ]
In addition to its normal cellular role, P-TEFb has been shown to be recruited by viral transactivator Tat to the nascent viral transcript, TAR, near the promoter to enhance viral transcription, which is required for efficient HIV-1 replication.
true
true
true
true
true
1,299
1
INTRODUCTION
1
19–22
[ "B17", "B18", "B19 B20 B21 B22", "B16", "B23", "B24", "B25", "B26", "B27", "B17", "B19", "B22", "B19", "B28 B29 B30 B31" ]
17,395,637
pmid-11713533|pmid-11713532|pmid-12832472|pmid-14580347|pmid-15713661|pmid-15713662|pmid-11545735|pmid-12177005|pmid-12944920|pmid-12037670|pmid-16109377|pmid-16109376|pmid-11713533|pmid-12832472|pmid-15713662|pmid-12832472|pmid-15514168|pmid-12695656|pmid-12368904|pmid-14749500|pmid-16382153|pmid-1646389|pmid-1646389
P-TEFb is uniquely regulated by the reversible association of a small nuclear RNA, 7SK (17,18) and one of two HEXIM proteins (19–22).
[ "17", "18", "19–22", "16", "23", "24", "25", "26", "27", "17", "19", "22", "19", "28–31" ]
133
7,997
1
false
P-TEFb is uniquely regulated by the reversible association of a small nuclear RNA, 7SK and one of two HEXIM proteins.
[ "17,18", "19–22" ]
P-TEFb is uniquely regulated by the reversible association of a small nuclear RNA, 7SK and one of two HEXIM proteins.
true
true
true
true
true
1,300
1
INTRODUCTION
1
17
[ "B17", "B18", "B19 B20 B21 B22", "B16", "B23", "B24", "B25", "B26", "B27", "B17", "B19", "B22", "B19", "B28 B29 B30 B31" ]
17,395,637
pmid-11713533|pmid-11713532|pmid-12832472|pmid-14580347|pmid-15713661|pmid-15713662|pmid-11545735|pmid-12177005|pmid-12944920|pmid-12037670|pmid-16109377|pmid-16109376|pmid-11713533|pmid-12832472|pmid-15713662|pmid-12832472|pmid-15514168|pmid-12695656|pmid-12368904|pmid-14749500|pmid-16382153|pmid-1646389|pmid-1646389
Glycerol gradient analyses of cell lysates indicate that two forms of P-TEFb exist in the cell.
[ "17", "18", "19–22", "16", "23", "24", "25", "26", "27", "17", "19", "22", "19", "28–31" ]
95
7,998
0
false
Glycerol gradient analyses of cell lysates indicate that two forms of P-TEFb exist in the cell.
[]
Glycerol gradient analyses of cell lysates indicate that two forms of P-TEFb exist in the cell.
true
true
true
true
true
1,300
1
INTRODUCTION
1
16
[ "B17", "B18", "B19 B20 B21 B22", "B16", "B23", "B24", "B25", "B26", "B27", "B17", "B19", "B22", "B19", "B28 B29 B30 B31" ]
17,395,637
pmid-11713533|pmid-11713532|pmid-12832472|pmid-14580347|pmid-15713661|pmid-15713662|pmid-11545735|pmid-12177005|pmid-12944920|pmid-12037670|pmid-16109377|pmid-16109376|pmid-11713533|pmid-12832472|pmid-15713662|pmid-12832472|pmid-15514168|pmid-12695656|pmid-12368904|pmid-14749500|pmid-16382153|pmid-1646389|pmid-1646389
An active form of P-TEFb, free of HEXIM and 7SK, interacts with a variety of cellular factors, including NF-κB (16), c-Myc (23,24), MyoD (25) and Brd4 (26,27), to regulate gene transcription.
[ "17", "18", "19–22", "16", "23", "24", "25", "26", "27", "17", "19", "22", "19", "28–31" ]
191
7,999
1
false
An active form of P-TEFb, free of HEXIM and 7SK, interacts with a variety of cellular factors, including NF-κB, c-Myc, MyoD and Brd4, to regulate gene transcription.
[ "16", "23,24", "25", "26,27" ]
An active form of P-TEFb, free of HEXIM and 7SK, interacts with a variety of cellular factors, including NF-κB, c-Myc, MyoD and Brd4, to regulate gene transcription.
true
true
true
true
true
1,300