Download Lez 26 Jan 2015

Distribuzione di sequenze nel genoma umano
Genoma Umano
3200 Mb
Geni e sequenze correlate
1200 Mb
Geni
48 Mb
Sequenze
correlate
1152 Mb
DNA intergenico
2000 Mb
Ripetizioni
intersperse
1400 Mb
Altre regioni
intergeniche
600 Mb
Pseudogeni
LINE
640 Mb
Microsatelliti
90 Mb
Frammenti genici
SINE
420 Mb
Varie
510 Mb
Introni, UTR
Elementi LTR
250 Mb
Trasposoni DNA
90 Mb
50 kb di genoma a confronto
Fattori trascrizionali in eucarioti
Tipi di ripetizione nel genoma umano

SINE



ALU
MIR
MIR3
1.558.000

1.090.000
393.000
75.000
Elementi LTR





LINE



868.000
LINE-1 516.000
LINE-2 315.000
LINE-3 37.000

Classe I ERV
Classe II ERV(K)
Classe III ERV(L)
MaLR
Trasposoni DNA




hAT
Tc-I
PiggyBac
N.C.
443.000
112.000
8.000
83.000
240.000
240.000
195.000
75.000
2.000
22.000
Confronto di interi genomi
Per aumentare l’affidabilità della predizione, si richiede che per
ogni coppia di ortologhi, ognuno dei due geni risulti quello più
simile all’altro quando confrontato con l’intero genoma
Genoma 1
Genoma2
se entrambe le relazioni sono vere ==> le due proteine
gialle si possono proporre come ortologhe
Tools for Comparative Genomics
Browser: This site contains the reference sequence and
• UCSC
working draft assemblies for a large collection of genomes.
The Ensembl project produces genome databases
• Ensembl:
for vertebrates and other eukaryotic species, and makes this
information freely available online.
The Map Viewer provides a wide variety of genome
• MapView:
mapping and sequencing data.[26]
A comprehensive suite of programs and databases for
• VISTA:
comparative analysis of genomic sequences. It was built to
visualize the results of comparative analysis based on DNA
alignments. The presentation of comparative data generated by
VISTA can easily suit both small and large scale of data.
COMPARATIVE GENOMICS AT THE VERTEBRATE EXTREMES
Dario Boffelli, Marcelo A. Nobrega and Edward M. Rubin
NATURE REVIEWS | GENETICS
VOLUME 5 | JUNE 2004 | 457
Annotators of the human genome are increasingly
exploiting comparisons with genomes at both the distal
and proximal evolutionary edges of the vertebrate tree.
Despite the sequence similarity between primates,
comparisons among members of this clade are
beginning to identify primate- as well as human-specific
functional elements. At the distal evolutionary extreme,
comparing the human genome to that of non-mammal
vertebrates such as fish has proved to be a powerful
filter to prioritize sequences that most probably have
significant functional activity in all vertebrates.
Conservation in enhancers shared by human and fish
A core enhancer in an intron
in DACH is >98% identical
for 350 bp in humans, mice
and rats. In the ~1 billion
years of parallel evolutionary
time that separates human,
mouse, rat, chicken, frog
and fish, only 6 substitutions
occurred in a 120-bp
fragment that corresponds to
an enhancer, 4 of which
occurred in the frog lineage
alone, and none occurred in
the mammalian lineage.
Defining functional DNA elements in the
human genome
Manolis Kellis et al.
PNAS April 29, 2014 | vol. 111 | no. 17 | 6131–6138
With the completion of the human genome sequence, attention turned to identifying and
annotating its functional DNA elements. As a complement to genetic and comparative
genomics approaches, the Encyclopedia of DNA Elements Project was launched to
contribute maps of RNA transcripts, transcriptional regulator binding sites, and
chromatin states in many cell types. The resulting genome-wide data reveal sites of
biochemical activity with high positional resolution and cell type specificity that facilitate
studies of gene regulation and interpretation of noncoding variants associated with
human disease. However, the biochemically active regions cover a much larger
fraction of the genome than do evolutionarily conserved regions, raising the
question of whether nonconserved but biochemically active regions are truly functional.
Here, we review the strengths and limitations of biochemical, evolutionary, and
genetic approaches for defining functional DNA segments, potential sources for the
observed differences in estimated genomic coverage, and the biological implications of
these discrepancies. We also analyze the relationship between signal intensity, genomic
coverage, and evolutionary conservation. Our results reinforce the principle that each
approach provides complementary information and that we need to use
combinations of all three to elucidate genome function in human biology and disease.
The complementary nature of evolutionary,
biochemical and genetic evidence
Encyclo pedia of DNA Elements
(ENCODE) Project
DNA that produces a
phenotype upon alteration
GERP++ elements from
34 mammal alignments
Epigenetic and evolutionary signals in cis-regulatory
modules (CRMs) of the HBB complex
Primate phylogenetic tree
Biomedical relevance
Specific differences in cytochrome P450 genes that are involved in drug
metabolism or other genetic components that are relevant to disease, such as
pathways involving the melanocortin receptor, methyltransferases and the
parathyroid hormone receptor 1.
Macaques have an expanded array of MHC class I genes that are central to
their response to infectious agents and other immune system processes.
Rhesus macaques carry variants in the ornithine carbamoyltransferase (OTC),
phenylalanine hydroxylase (PAH) and N-acetylglucosaminidase alpha
(NAGLU) genes that predispose some human individuals to disease.
Chimpanzees carry ‘disease’ alleles in genes that are related to cancer (mutL
homologue 1 (MLH1)), diabetes mellitus (peroxi- some proliferator-activated
receptor g (PPARG)) and Alzheimer’s disease (apolipoprotein E (APOE)).
Transcriptomics. Expression of drug-metabolizing P450 genes and some
amino acid sequences differ between cynomolgus and rhesus macaques98,
which has implications for pharmacokinetics.
Lo “switch” fetale-adulto nel locus delle -globine
Il locus Albumina / Alfa-fetoproteina (ALB/AFP)
Hind III
(AAGCTT)
13.4
5
10
13.5
45.9 46.3 47.8 48.2
15
20
25
30
35
40
50
45
55
60
III II
ALB Prom
inattive
ALB Prom
AFP +
AFP -
ALB -
ALB +
III II
Ealb Eafp
Before birth
Eafp
AFP Prom
AFP Prom
ACTIVE
AFP Prom
inactive
III II
Ealb
Eafp
ALB Prom
After birth
ACTIVE
x
Ealb
x
Kb
Sau3A
(GATC)
3C “Carbon Copy” (5C)
Hi-C, a method that probes the three-dimensional
architecture of whole genomes
Cut with
restriction
enzyme
Fill ends
and mark
with biotin
Ligate
blunt ends
Crosslink
DNA
Purify and
shear DNA
Sequence
paired-ends
Pull down
biotin
Map of chromosome 14 at 1Mb resolution
(A) The map of chromosome 14 at 1Mb
resolution exhibits substructure in the form
of an intense diagonal and a constellation of
large blocks
The Observed/expected matrix (B) shows
loci with either more (red) or less (blue)
interactions than would be expected given
their genomic distance (range: 0.2 – 5).
Correlation map of chromosome 14 at a
resolution of 100kb
The principal component (eigenvector) correlates with the
distribution of genes and with features of open chromatin.
Genome architecture at three scales
Two compartments,
corresponding to
open and closed
chromatin, spatially
partition the genome.
Chromosomes (blue,
cyan, green) occupy
distinct territories.
Individual
chromosomes weave
back-and-forth
between the open
and closed chromatin
compartments.
At the scale of single
megabases, the
chromosome
consists of a series
of fractal globules.
Prof. Vincenzo De Simone
Analisi del Trascrittoma mediante
Microarrays a DNA
3
Lezione n.
Parole chiave:
Microarrays, Gene
Chips, Trascrittoma.
Corso di Laurea:
AgroBiotecnologie,
Biotecnol. Mediche
Insegnamento:
Biologia Molecolare
Avanzata
Email Docente:
vincenzo.desimone@
A.A. 2009-2010
unina.it
Prof. Vincenzo De Simone
Un esempio di studio comparato del
Trascrittoma mediante Microarrays a DNA
4
Lezione n.
Parole chiave:
Microarrays,
trascrittoma, profili di
espressione genica.
Corso di Laurea:
AgroBiotecnologie
Biotecnol. Mediche
Insegnamento:
Biologia Molecolare
Avanzata
Email Docente:
vincenzo.desimone@
A.A. 2009-2010
unina.it
Conclusioni
• Struttura e composizione dei genomi.
• Sequenze ripetute nel genoma umano.
• Gli strumenti per il confronto tra genomi.
• Identificazione di CRMs (Cis Regulatory Modules) per
confronto tra genomi agli estremi dell’albero evolutivo dei
vertebrati.
• Identificazione di CRMs mediante approcci multidisciplinari
(biochimica, genetica, genomica e trascrittomica comparativa).
• Genomica comparativa dei primati ed identificazione di regioni
a velocità evolutiva variabile e di alleli utili per patologie umane.
• Interazioni tra regioni genomiche distanti e metodiche 3/5/HiC.
• Il pacchetto VISTA per la genomica comparativa.
• Il Genome Browser UCSC