INVESTIGADORES
FERNANDEZ Paula Del Carmen
artículos
Título:
Differential representation of sunflower ESTs in enriched organ-specific cDNA libraries in a small scale sequencing project
Autor/es:
FERNANDEZ, P.; PANIEGO, N.; LEW, S.; HOPP, H.E.; HEINZ, R.
Revista:
BMC GENOMICS
Editorial:
BioMed Central
Referencias:
Lugar: Londres; Año: 2003 p. 4 - 40
ISSN:
1471-2164
Resumen:
Background: Subtractive hybridization methods are valuable tools for identifying differentially
regulated genes in a given tissue avoiding redundant sequencing of clones representing the same
expressed genes, maximizing detection of low abundant transcripts and thus, affecting the efficiency
and cost effectiveness of small scale cDNA sequencing projects aimed to the specific identification
of useful genes for breeding purposes. The objective of this work is to evaluate alternative
strategies to high-throughput sequencing projects for the identification of novel genes differentially
expressed in sunflower as a source of organ-specific genetic markers that can be functionally
associated to important traits.
regulated genes in a given tissue avoiding redundant sequencing of clones representing the same
expressed genes, maximizing detection of low abundant transcripts and thus, affecting the efficiency
and cost effectiveness of small scale cDNA sequencing projects aimed to the specific identification
of useful genes for breeding purposes. The objective of this work is to evaluate alternative
strategies to high-throughput sequencing projects for the identification of novel genes differentially
expressed in sunflower as a source of organ-specific genetic markers that can be functionally
associated to important traits.
regulated genes in a given tissue avoiding redundant sequencing of clones representing the same
expressed genes, maximizing detection of low abundant transcripts and thus, affecting the efficiency
and cost effectiveness of small scale cDNA sequencing projects aimed to the specific identification
of useful genes for breeding purposes. The objective of this work is to evaluate alternative
strategies to high-throughput sequencing projects for the identification of novel genes differentially
expressed in sunflower as a source of organ-specific genetic markers that can be functionally
associated to important traits.
regulated genes in a given tissue avoiding redundant sequencing of clones representing the same
expressed genes, maximizing detection of low abundant transcripts and thus, affecting the efficiency
and cost effectiveness of small scale cDNA sequencing projects aimed to the specific identification
of useful genes for breeding purposes. The objective of this work is to evaluate alternative
strategies to high-throughput sequencing projects for the identification of novel genes differentially
expressed in sunflower as a source of organ-specific genetic markers that can be functionally
associated to important traits.
regulated genes in a given tissue avoiding redundant sequencing of clones representing the same
expressed genes, maximizing detection of low abundant transcripts and thus, affecting the efficiency
and cost effectiveness of small scale cDNA sequencing projects aimed to the specific identification
of useful genes for breeding purposes. The objective of this work is to evaluate alternative
strategies to high-throughput sequencing projects for the identification of novel genes differentially
expressed in sunflower as a source of organ-specific genetic markers that can be functionally
associated to important traits.
regulated genes in a given tissue avoiding redundant sequencing of clones representing the same
expressed genes, maximizing detection of low abundant transcripts and thus, affecting the efficiency
and cost effectiveness of small scale cDNA sequencing projects aimed to the specific identification
of useful genes for breeding purposes. The objective of this work is to evaluate alternative
strategies to high-throughput sequencing projects for the identification of novel genes differentially
expressed in sunflower as a source of organ-specific genetic markers that can be functionally
associated to important traits.
regulated genes in a given tissue avoiding redundant sequencing of clones representing the same
expressed genes, maximizing detection of low abundant transcripts and thus, affecting the efficiency
and cost effectiveness of small scale cDNA sequencing projects aimed to the specific identification
of useful genes for breeding purposes. The objective of this work is to evaluate alternative
strategies to high-throughput sequencing projects for the identification of novel genes differentially
expressed in sunflower as a source of organ-specific genetic markers that can be functionally
associated to important traits.
Subtractive hybridization methods are valuable tools for identifying differentially
regulated genes in a given tissue avoiding redundant sequencing of clones representing the same
expressed genes, maximizing detection of low abundant transcripts and thus, affecting the efficiency
and cost effectiveness of small scale cDNA sequencing projects aimed to the specific identification
of useful genes for breeding purposes. The objective of this work is to evaluate alternative
strategies to high-throughput sequencing projects for the identification of novel genes differentially
expressed in sunflower as a source of organ-specific genetic markers that can be functionally
associated to important traits.
Results: Differential organ-specific ESTs were generated from leaf, stem, root and flower bud at
two developmental stages (R1 and R4). The use of different sources of RNA as tester and driver
cDNA for the construction of differential libraries was evaluated as a tool for detection of rare or
low abundant transcripts. Organ-specificity ranged from 75 to 100% of non-redundant sequences
in the different cDNA libraries. Sequence redundancy varied according to the target and driver
cDNA used in each case. The R4 flower cDNA library was the less redundant library with 62% of
unique sequences. Out of a total of 919 sequences that were edited and annotated, 318 were nonredundant
sequences. Comparison against sequences in public databases showed that 60% of nonredundant
sequences showed significant similarity to known sequences. The number of predicted
novel genes varied among the different cDNA libraries, ranging from 56% in the R4 flower to 16 %
in the R1 flower bud library. Comparison with sunflower ESTs on public databases showed that
197 of non-redundant sequences (60%) did not exhibit significant similarity to previously reported
sunflower ESTs. This approach helped to successfully isolate a significant number of new reported
sequences putatively related to responses to important agronomic traits and key regulatory and
physiological genes.
two developmental stages (R1 and R4). The use of different sources of RNA as tester and driver
cDNA for the construction of differential libraries was evaluated as a tool for detection of rare or
low abundant transcripts. Organ-specificity ranged from 75 to 100% of non-redundant sequences
in the different cDNA libraries. Sequence redundancy varied according to the target and driver
cDNA used in each case. The R4 flower cDNA library was the less redundant library with 62% of
unique sequences. Out of a total of 919 sequences that were edited and annotated, 318 were nonredundant
sequences. Comparison against sequences in public databases showed that 60% of nonredundant
sequences showed significant similarity to known sequences. The number of predicted
novel genes varied among the different cDNA libraries, ranging from 56% in the R4 flower to 16 %
in the R1 flower bud library. Comparison with sunflower ESTs on public databases showed that
197 of non-redundant sequences (60%) did not exhibit significant similarity to previously reported
sunflower ESTs. This approach helped to successfully isolate a significant number of new reported
sequences putatively related to responses to important agronomic traits and key regulatory and
physiological genes.
two developmental stages (R1 and R4). The use of different sources of RNA as tester and driver
cDNA for the construction of differential libraries was evaluated as a tool for detection of rare or
low abundant transcripts. Organ-specificity ranged from 75 to 100% of non-redundant sequences
in the different cDNA libraries. Sequence redundancy varied according to the target and driver
cDNA used in each case. The R4 flower cDNA library was the less redundant library with 62% of
unique sequences. Out of a total of 919 sequences that were edited and annotated, 318 were nonredundant
sequences. Comparison against sequences in public databases showed that 60% of nonredundant
sequences showed significant similarity to known sequences. The number of predicted
novel genes varied among the different cDNA libraries, ranging from 56% in the R4 flower to 16 %
in the R1 flower bud library. Comparison with sunflower ESTs on public databases showed that
197 of non-redundant sequences (60%) did not exhibit significant similarity to previously reported
sunflower ESTs. This approach helped to successfully isolate a significant number of new reported
sequences putatively related to responses to important agronomic traits and key regulatory and
physiological genes.
two developmental stages (R1 and R4). The use of different sources of RNA as tester and driver
cDNA for the construction of differential libraries was evaluated as a tool for detection of rare or
low abundant transcripts. Organ-specificity ranged from 75 to 100% of non-redundant sequences
in the different cDNA libraries. Sequence redundancy varied according to the target and driver
cDNA used in each case. The R4 flower cDNA library was the less redundant library with 62% of
unique sequences. Out of a total of 919 sequences that were edited and annotated, 318 were nonredundant
sequences. Comparison against sequences in public databases showed that 60% of nonredundant
sequences showed significant similarity to known sequences. The number of predicted
novel genes varied among the different cDNA libraries, ranging from 56% in the R4 flower to 16 %
in the R1 flower bud library. Comparison with sunflower ESTs on public databases showed that
197 of non-redundant sequences (60%) did not exhibit significant similarity to previously reported
sunflower ESTs. This approach helped to successfully isolate a significant number of new reported
sequences putatively related to responses to important agronomic traits and key regulatory and
physiological genes.
two developmental stages (R1 and R4). The use of different sources of RNA as tester and driver
cDNA for the construction of differential libraries was evaluated as a tool for detection of rare or
low abundant transcripts. Organ-specificity ranged from 75 to 100% of non-redundant sequences
in the different cDNA libraries. Sequence redundancy varied according to the target and driver
cDNA used in each case. The R4 flower cDNA library was the less redundant library with 62% of
unique sequences. Out of a total of 919 sequences that were edited and annotated, 318 were nonredundant
sequences. Comparison against sequences in public databases showed that 60% of nonredundant
sequences showed significant similarity to known sequences. The number of predicted
novel genes varied among the different cDNA libraries, ranging from 56% in the R4 flower to 16 %
in the R1 flower bud library. Comparison with sunflower ESTs on public databases showed that
197 of non-redundant sequences (60%) did not exhibit significant similarity to previously reported
sunflower ESTs. This approach helped to successfully isolate a significant number of new reported
sequences putatively related to responses to important agronomic traits and key regulatory and
physiological genes.
two developmental stages (R1 and R4). The use of different sources of RNA as tester and driver
cDNA for the construction of differential libraries was evaluated as a tool for detection of rare or
low abundant transcripts. Organ-specificity ranged from 75 to 100% of non-redundant sequences
in the different cDNA libraries. Sequence redundancy varied according to the target and driver
cDNA used in each case. The R4 flower cDNA library was the less redundant library with 62% of
unique sequences. Out of a total of 919 sequences that were edited and annotated, 318 were nonredundant
sequences. Comparison against sequences in public databases showed that 60% of nonredundant
sequences showed significant similarity to known sequences. The number of predicted
novel genes varied among the different cDNA libraries, ranging from 56% in the R4 flower to 16 %
in the R1 flower bud library. Comparison with sunflower ESTs on public databases showed that
197 of non-redundant sequences (60%) did not exhibit significant similarity to previously reported
sunflower ESTs. This approach helped to successfully isolate a significant number of new reported
sequences putatively related to responses to important agronomic traits and key regulatory and
physiological genes.
two developmental stages (R1 and R4). The use of different sources of RNA as tester and driver
cDNA for the construction of differential libraries was evaluated as a tool for detection of rare or
low abundant transcripts. Organ-specificity ranged from 75 to 100% of non-redundant sequences
in the different cDNA libraries. Sequence redundancy varied according to the target and driver
cDNA used in each case. The R4 flower cDNA library was the less redundant library with 62% of
unique sequences. Out of a total of 919 sequences that were edited and annotated, 318 were nonredundant
sequences. Comparison against sequences in public databases showed that 60% of nonredundant
sequences showed significant similarity to known sequences. The number of predicted
novel genes varied among the different cDNA libraries, ranging from 56% in the R4 flower to 16 %
in the R1 flower bud library. Comparison with sunflower ESTs on public databases showed that
197 of non-redundant sequences (60%) did not exhibit significant similarity to previously reported
sunflower ESTs. This approach helped to successfully isolate a significant number of new reported
sequences putatively related to responses to important agronomic traits and key regulatory and
physiological genes.
Differential organ-specific ESTs were generated from leaf, stem, root and flower bud at
two developmental stages (R1 and R4). The use of different sources of RNA as tester and driver
cDNA for the construction of differential libraries was evaluated as a tool for detection of rare or
low abundant transcripts. Organ-specificity ranged from 75 to 100% of non-redundant sequences
in the different cDNA libraries. Sequence redundancy varied according to the target and driver
cDNA used in each case. The R4 flower cDNA library was the less redundant library with 62% of
unique sequences. Out of a total of 919 sequences that were edited and annotated, 318 were nonredundant
sequences. Comparison against sequences in public databases showed that 60% of nonredundant
sequences showed significant similarity to known sequences. The number of predicted
novel genes varied among the different cDNA libraries, ranging from 56% in the R4 flower to 16 %
in the R1 flower bud library. Comparison with sunflower ESTs on public databases showed that
197 of non-redundant sequences (60%) did not exhibit significant similarity to previously reported
sunflower ESTs. This approach helped to successfully isolate a significant number of new reported
sequences putatively related to responses to important agronomic traits and key regulatory and
physiological genes.
Conclusions: The application of suppressed subtracted hybridization technology not only enabled
the cost effective isolation of differentially expressed sequences but it also allowed the
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
the cost effective isolation of differentially expressed sequences but it also allowed the
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
the cost effective isolation of differentially expressed sequences but it also allowed the
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
the cost effective isolation of differentially expressed sequences but it also allowed the
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
the cost effective isolation of differentially expressed sequences but it also allowed the
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
the cost effective isolation of differentially expressed sequences but it also allowed the
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
the cost effective isolation of differentially expressed sequences but it also allowed the
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
The application of suppressed subtracted hybridization technology not only enabled
the cost effective isolation of differentially expressed sequences but it also allowed the
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.
identification of novel sequences in sunflower from a relative small number of analyzed sequences
when compared to major sequencing projects.