An intron is any nucleotide sequence within a gene that is not expressed or operative in the final RNA product. The word intron is derived from the term intragenic region, i.e., a region inside a gene. The term intron refers to both the DNA sequence within a gene and the corresponding RNA sequence in RNA transcripts. The non-intron sequences that become joined by this RNA processing to form the mature RNA are called exons.
Introns are found in the genes of most organisms and many viruses
and they can be located in both protein-coding genes and genes that
function as RNA (noncoding genes). There are four main types of introns:
tRNA introns, group I introns, group II introns, and spliceosomal
introns (see below). Introns are rare in Bacteria and Archaea
(prokaryotes), but most eukaryotic genes contain multiple spliceosomal
introns.
Discovery and etymology
Introns were first discovered in protein-coding genes of adenovirus,
and were subsequently identified in genes encoding transfer RNA and
ribosomal RNA genes. Introns are now known to occur within a wide
variety of genes throughout organisms, bacteria, and viruses within all of the biological kingdoms.
"The notion of the cistron
[i.e., gene] ... must be replaced by that of a transcription unit
containing regions which will be lost from the mature messenger – which I
suggest we call introns (for intragenic regions) – alternating with
regions which will be expressed – exons." (Gilbert 1978)
The term intron also refers to intracistron, i.e., an additional piece of DNA that arises within a cistron.
Although introns are sometimes called intervening sequences,
the term "intervening sequence" can refer to any of several families of
internal nucleic acid sequences that are not present in the final gene
product, including inteins, untranslated regions (UTR), and nucleotides removed by RNA editing, in addition to introns.
Distribution
The
frequency of introns within different genomes is observed to vary
widely across the spectrum of biological organisms. For example, introns
are extremely common within the nuclear genome of jawed vertebrates
(e.g. humans, mice, and pufferfish (fugu)), where protein-coding genes
almost always contain multiple introns, while introns are rare within
the nuclear genes of some eukaryotic microorganisms, for example baker's/brewer's yeast (Saccharomyces cerevisiae). In contrast, the mitochondrial genomes of vertebrates are entirely devoid of introns, while those of eukaryotic microorganisms may contain many introns.
Simple
illustration of an unspliced mRNA precursor, with two introns and three
exons (top). After the introns have been removed via splicing, the
mature mRNA sequence is ready for translation (bottom).
A particularly extreme case is the Drosophila dhc7 gene containing a ≥3.6 megabase (Mb) intron, which takes roughly three days to transcribe.
On the other extreme, a 2015 study suggests that the shortest known
metazoan intron length is 30 base pairs (bp) belonging to the human MST1L gene. The shortest known introns belong to the heterotrich ciliates, such as Stentor coeruleus, in which most (> 95%) introns are 15 or 16 bp long.
Classification
Splicing
of all intron-containing RNA molecules is superficially similar, as
described above. However, different types of introns were identified
through the examination of intron structure by DNA sequence analysis,
together with genetic and biochemical analysis of RNA splicing
reactions. At least four distinct classes of introns have been
identified:
Self-splicing group II introns that are removed by RNA catalysis
Group III introns
are proposed to be a fifth family, but little is known about the
biochemical apparatus that mediates their splicing. They appear to be
related to group II introns, and possibly to spliceosomal introns.
Nuclear pre-mRNA introns (spliceosomal introns) are characterized by
specific intron sequences located at the boundaries between introns and
exons. These sequences are recognized by spliceosomal RNA molecules when the splicing reactions are initiated.
In addition, they contain a branch point, a particular nucleotide
sequence near the 3' end of the intron that becomes covalently linked to
the 5' end of the intron during the splicing process, generating a
branched (lariat) intron. Apart from these three short conserved
elements, nuclear pre-mRNA intron sequences are highly variable. Nuclear
pre-mRNA introns are often much longer than their surrounding exons.
tRNA introns
Transfer
RNA introns that depend upon proteins for removal occur at a specific
location within the anticodon loop of unspliced tRNA precursors, and are
removed by a tRNA splicing endonuclease. The exons are then linked
together by a second protein, the tRNA splicing ligase. Note that self-splicing introns are also sometimes found within tRNA genes.
Group I and group II introns are found in genes encoding proteins (messenger RNA), transfer RNA and ribosomal RNA in a very wide range of living organisms. Following transcription into RNA, group I and group II introns also
make extensive internal interactions that allow them to fold into a
specific, complex three-dimensional architecture. These complex architectures allow some group I and group II introns to be self-splicing,
that is, the intron-containing RNA molecule can rearrange its own
covalent structure so as to precisely remove the intron and link the
exons together in the correct order. In some cases, particular
intron-binding proteins are involved in splicing, acting in such a way
that they assist the intron in folding into the three-dimensional
structure that is necessary for self-splicing activity. Group I and
group II introns are distinguished by different sets of internal
conserved sequences and folded structures, and by the fact that splicing
of RNA molecules containing group II introns generates branched introns
(like those of spliceosomal RNAs), while group I introns use a
non-encoded guanosine nucleotide (typically GTP) to initiate splicing,
adding it on to the 5'-end of the excised intron.
On the accuracy of splicing
The
spliceosome is a very complex structure containing up to one hundred
proteins and five different RNAs. The substrate of the reaction is a
long RNA molecule and the transesterification reactions catalyzed by the
spliceosome require the bringing together of sites that may be
thousands of nucleotides apart.
All biochemical reactions are associated with known error rates and the
more complicated the reaction the higher the error rate. Therefore, it
is not surprising that the splicing reaction catalyzed by the
spliceosome has a significant error rate even though there are
spliceosome accessory factors that suppress the accidental cleavage of
cryptic splice sites.
Under ideal circumstances, the splicing reaction is likely to be 99.999% accurate (error rate of 10−5) and the correct exons will be joined and the correct intron will be deleted.
However, these ideal conditions require very close matches to the best
splice site sequences and the absence of any competing cryptic splice
site sequences within the introns and those conditions are rarely met in
large eukaryotic genes that may cover more than 40 kilobase pairs.
Recent studies have shown that the actual error rate can be considerably
higher than 10−5 and may be as high as 2% or 3% errors (error rate of 2 or 3 x 10−2) per gene. Additional studies suggest that the error rate is no less than 0.1% per intron.
This relatively high level of splicing errors explains why most splice
variants are rapidly degraded by nonsense-mediated decay.
The presence of sloppy binding sites within genes causes splicing
errors and it may seem strange that these sites haven't been eliminated
by natural selection. The argument for their persistence is similar to
the argument for junk DNA.
Although mutations which create or disrupt binding sites
may be slightly deleterious, the large number of possible such mutations
makes it inevitable that some will reach fixation in a population. This
is particularly relevant in species, such as humans, with relatively
small long-term effective population sizes. It is plausible, then, that
the human genome carries a substantial load of suboptimal sequences
which cause the generation of aberrant transcript isoforms. In this
study, we present direct evidence that this is indeed the case.
While the catalytic reaction may be accurate enough for effective
processing most of the time, the overall error rate may be partly
limited by the fidelity of transcription because transcription errors
will introduce mutations that create cryptic splice sites. In addition,
the transcription error rate of 10−5 – 10−6 is
high enough that one in every 25,000 transcribed exons will have an
incorporation error in one of the splice sites leading to a skipped
intron or a skipped exon. Almost all multi-exon genes will produce
incorrectly spliced transcripts but the frequency of this background
noise will depend on the size of the genes, the number of introns, and
the quality of the splice site sequences.
In some cases, splice variants will be produced by mutations in
the gene (DNA). These can be SNP polymorphisms that create a cryptic
splice site or mutate a functional site. They can also be somatic cell
mutations that affect splicing in a particular tissue or a cell line.
When the mutant allele is in a heterozygous state this will result in
production of two abundant splice variants; one functional and one
non-functional. In the homozygous state the mutant alleles may cause a
genetic disease such as the hemophilia found in descendants of Queen
Victoria where a mutation in one of the introns in a blood clotting
factor gene creates a cryptic 3' splice site resulting in aberrant
splicing.
A significant fraction of human deaths by disease may be caused by
mutations that interfere with normal splicing; mostly by creating
cryptic splice sites.
Incorrectly spliced transcripts can easily be detected and their
sequences entered into the online databases. They are usually described
as "alternatively spliced" transcripts, which can be confusing because
the term does not distinguish between real, biologically relevant,
alternative splicing and processing noise due to splicing errors. One of
the central issues in the field of alternative splicing is working out
the differences between these two possibilities. Many scientists have
argued that the null hypothesis should be splicing noise, putting the
burden of proof on those who claim biologically relevant alternative
splicing. According to those scientists, the claim of function must be
accompanied by convincing evidence that multiple functional products are
produced from the same gene.
Biological functions and evolution
While
introns do not encode protein products, they are integral to gene
expression regulation. Some introns themselves encode functional RNAs
through further processing after splicing to generate noncoding RNA molecules. Alternative splicing
is widely used to generate multiple proteins from a single gene.
Furthermore, some introns play essential roles in a wide range of gene
expression regulatory functions such as nonsense-mediated decay and mRNA export.
After the initial discovery of introns in protein-coding genes of
the eukaryotic nucleus, there was significant debate as to whether
introns in modern-day organisms were inherited from a common ancient
ancestor (termed the introns-early hypothesis), or whether they appeared
in genes rather recently in the evolutionary process (termed the
introns-late hypothesis). Another theory is that the spliceosome and the intron-exon structure of genes is a relic of the RNA world (the introns-first hypothesis).
There is still considerable debate about the extent to which of these
hypotheses is most correct but the popular consensus at the moment is
that following the formation of the first eukaryotic cell, group II
introns from the bacterial endosymbiont invaded the host genome. In the
beginning these self-splicing introns excised themselves from the mRNA
precursor but over time some of them lost that ability and their
excision had to be aided in trans by other group II introns.
Eventually a number of specific trans-acting introns evolved and these
became the precursors to the snRNAs of the spliceosome. The efficiency
of splicing was improved by association with stabilizing proteins to
form the primitive spliceosome.
Early studies of genomic DNA sequences from a wide range of
organisms show that the intron-exon structure of homologous genes in
different organisms can vary widely. More recent studies of entire eukaryoticgenomes
have now shown that the lengths and density (introns/gene) of introns
varies considerably between related species. For example, while the
human genome contains an average of 8.4 introns/gene (139,418 in the
genome), the unicellular fungus Encephalitozoon cuniculi contains only 0.0075 introns/gene (15 introns in the genome). Since eukaryotes arose from a common ancestor (common descent), there must have been extensive gain or loss of introns during evolutionary time.
This process is thought to be subject to selection, with a tendency
towards intron gain in larger species due to their smaller population
sizes, and the converse in smaller (particularly unicellular) species. Biological factors also influence which genes in a genome lose or accumulate introns.
Alternative splicing
of exons within a gene after intron excision acts to introduce greater
variability of protein sequences translated from a single gene, allowing
multiple related proteins to be generated from a single gene and a
single precursor mRNA transcript. The control of alternative RNA
splicing is performed by a complex network of signaling molecules that
respond to a wide range of intracellular and extracellular signals.
Introns contain several short sequences that are important for
efficient splicing, such as acceptor and donor sites at either end of
the intron as well as a branch point site, which are required for proper
splicing by the spliceosome. Some introns are known to enhance the expression of the gene that they are contained in by a process known as intron-mediated enhancement (IME).
Actively transcribed regions of DNA frequently form R-loops that are vulnerable to DNA damage. In highly expressed yeast genes, introns inhibit R-loop formation and the occurrence of DNA damage.
Genome-wide analysis in both yeast and humans revealed that
intron-containing genes have decreased R-loop levels and decreased DNA
damage compared to intronless genes of similar expression. Insertion of an intron within an R-loop prone gene can also suppress R-loop formation and recombination. Bonnet et al. (2017)
speculated that the function of introns in maintaining genetic
stability may explain their evolutionary maintenance at certain
locations, particularly in highly expressed genes.
Starvation adaptation
The
physical presence of introns promotes cellular resistance to starvation
via intron enhanced repression of ribosomal protein genes of
nutrient-sensing pathways.
As mobile genetic elements
Introns may be lost or gained over evolutionary time, as shown by many comparative studies of orthologous
genes. Subsequent analyses have identified thousands of examples of
intron loss and gain events, and it has been proposed that the emergence
of eukaryotes, or the initial stages of eukaryotic evolution, involved
an intron invasion.
Two definitive mechanisms of intron loss, reverse
transcriptase-mediated intron loss (RTMIL) and genomic deletions, have
been identified, and are known to occur.
The definitive mechanisms of intron gain, however, remain elusive and
controversial. At least seven mechanisms of intron gain have been
reported thus far: intron transposition, transposon insertion, tandem
genomic duplication, intron transfer, intron gain during double-strand
break repair (DSBR), insertion of a group II intron, and intronization.
In theory it should be easiest to deduce the origin of recently gained
introns due to the lack of host-induced mutations, yet even introns
gained recently did not arise from any of the aforementioned mechanisms.
These findings thus raise the question of whether or not the proposed
mechanisms of intron gain fail to describe the mechanistic origin of
many novel introns because they are not accurate mechanisms of intron
gain, or if there are other, yet to be discovered, processes generating
novel introns.
In intron transposition, the most commonly purported intron gain
mechanism, a spliced intron is thought to reverse splice into either its
own mRNA or another mRNA at a previously intron-less position. This
intron-containing mRNA is then reverse transcribed and the resulting
intron-containing cDNA may then cause intron gain via complete or
partial recombination with its original genomic locus. Transposon
insertions can also result in intron creation. Such an insertion could
intronize the transposon without disrupting the coding sequence when a
transposon inserts into the sequence AGGT, resulting in the duplication
of this sequence on each side of the transposon. It is not yet
understood why these elements are spliced, whether by chance, or by some
preferential action by the transposon. In tandem genomic duplication,
due to the similarity between consensus donor and acceptor splice sites,
which both closely resemble AGGT, the tandem genomic duplication of an
exonic segment harboring an AGGT sequence generates two potential splice
sites. When recognized by the spliceosome, the sequence between the
original and duplicated AGGT will be spliced, resulting in the creation
of an intron without alteration of the coding sequence of the gene.
Double-stranded break repair via non-homologous end joining was recently
identified as a source of intron gain when researchers identified short
direct repeats flanking 43% of gained introns in Daphnia.
These numbers must be compared to the number of conserved introns
flanked by repeats in other organisms, though, for statistical
relevance. For group II intron insertion, the retrohoming of a group II
intron into a nuclear gene was proposed to cause recent spliceosomal
intron gain.
Intron transfer has been hypothesized to result in intron gain
when a paralog or pseudogene gains an intron and then transfers this
intron via recombination to an intron-absent location in its sister
paralog. Intronization is the process by which mutations create novel
introns from formerly exonic sequence. Thus, unlike other proposed
mechanisms of intron gain, this mechanism does not require the insertion
or generation of DNA to create a novel intron.
The only hypothesized mechanism of recent intron gain lacking any
direct evidence is that of group II intron insertion, which when
demonstrated in vivo, abolishes gene expression.
Group II introns are therefore likely the presumed ancestors of
spliceosomal introns, acting as site-specific retroelements, and are no
longer responsible for intron gain.
Tandem genomic duplication is the only proposed mechanism with
supporting in vivo experimental evidence: a short intragenic tandem
duplication can insert a novel intron into a protein-coding gene,
leaving the corresponding peptide sequence unchanged.
This mechanism also has extensive indirect evidence lending support to
the idea that tandem genomic duplication is a prevalent mechanism for
intron gain. The testing of other proposed mechanisms in vivo,
particularly intron gain during DSBR, intron transfer, and
intronization, is possible, although these mechanisms must be
demonstrated in vivo to solidify them as actual mechanisms of intron
gain. Further genomic analyses, especially when executed at the
population level, may then quantify the relative contribution of each
mechanism, possibly identifying species-specific biases that may shed
light on varied rates of intron gain amongst different species.
Schematic representation of the human diploid karyotype, showing the organization of the genome into chromosomes, as well as annotated bands and sub-bands as seen on G banding. This drawing shows both the female (XX) and male (XY) versions of the 23rd chromosome pair. Chromosomal changes during the cell cycle are displayed at top center. The mitochondrial genome is shown to scale at bottom left.
While there are significant differences among the genomes of human individuals (on the order of 0.1% due to single-nucleotide variants and 0.6% when considering indels), these are considerably smaller than the differences between humans and their closest living relatives, the bonobos and chimpanzees (~1.1% fixed single-nucleotide variants and 4% when including indels). Size in basepairs can vary too; the telomere length decreases after every round of DNA replication.
Although the sequence of the human genome has been completely determined by DNA sequencing in 2022 (including methylation), it is not yet fully understood. Most, but not all, genes have been identified by a combination of high throughput experimental and bioinformatics approaches, yet much work still needs to be done to further elucidate the biological functions of their protein and RNA products (in particular, annotation of the complete CHM13v2.0 sequence is still ongoing). And yet, overlapping genes
are quite common, in some cases allowing two protein coding genes from
each strand to reuse base pairs twice (for example, genes DCDC2 and
KAAG1).
Recent results suggest that most of the vast quantities of noncoding
DNA within the genome have associated biochemical activities, including regulation of gene expression, organization of chromosome architecture, and signals controlling epigenetic inheritance. There are also a significant number of retroviruses in human DNA, at least 3 of which have been proven to possess an important function (i.e., HIV-like HERV-K, HERV-W, and HERV-FRD play a role in placenta formation by inducing cell-cell fusion).
In 2003, scientists reported the sequencing of 85% of the entire human genome, but as of 2020 at least 8% was still missing. In 2021, scientists reported sequencing the complete female genome (i.e., without the Y chromosome). This sequence identified 19,969 protein-coding sequences, accounting for approximately 1.5% of the genome, and 63,494 genes in total, most of them being non-coding RNA genes. The genome consists of regulatory DNA sequences, LINEs, SINEs, introns, and sequences for which as yet no function has been determined. The human Y chromosome,
consisting of 62,460,029 base pairs from a different cell line and
found in all males, was sequenced completely in January 2022.
In 2023, a draft human pangenome reference was published. It is based on 47 genomes from persons of varied ethnicity. Plans are underway for an improved reference capturing still more biodiversity from a still wider sample.
Sequencing
The first human genome sequences were published in nearly complete draft form in February 2001 by the Human Genome Project and Celera Corporation.
Completion of the Human Genome Project's sequencing effort was
announced in 2004 with the publication of a draft genome sequence,
leaving just 341 gaps in the sequence, representing highly repetitive
and other DNA that could not be sequenced with the technology available
at the time.
The human genome was the first of all vertebrates to be sequenced to
such near-completion, and as of 2018, the diploid genomes of over a
million individual humans had been determined using next-generation sequencing.
These data are used worldwide in biomedical science, anthropology, forensics
and other branches of science. Such genomic studies have led to
advances in the diagnosis and treatment of diseases, and to new insights
in many fields of biology, including human evolution.
By 2018, the total number of genes had been raised to at least 46,831, plus another 2300 micro-RNA genes. A 2018 population survey found another 300 million bases of human genome that was not in the reference sequence.
Prior to the acquisition of the full genome sequence, estimates of the
number of human genes ranged from 50,000 to 140,000 (with occasional
vagueness about whether these estimates included non-protein coding
genes). As genome sequence quality and the methods for identifying protein-coding genes improved, the count of recognized protein-coding genes dropped to 19,000–20,000.
In June 2016, scientists formally announced HGP-Write, a plan to synthesize the human genome.
In 2022 the Telomere-to-Telomere (T2T) consortium reported the complete sequence of a human female genome, filling all the gaps in the X chromosome (2020) and the 22 autosomes (May 2021). The previously unsequenced parts contain immune response genes that help to adapt to and survive infections, as well as genes that are important for predicting drug response.
The completed human genome sequence will also provide better
understanding of human formation as an individual organism and how
humans vary both between each other and other species.
Although the 'completion' of the human genome project was announced in 2001,
there remained hundreds of gaps, with about 5–10% of the total sequence
remaining undetermined. The missing genetic information was mostly in
repetitive heterochromatic regions and near the centromeres and telomeres, but also some gene-encoding euchromatic regions.
There remained 160 euchromatic gaps in 2015 when the sequences spanning
another 50 formerly unsequenced regions were determined. Only in 2020 was the first truly complete telomere-to-telomere sequence of a human chromosome determined, namely of the X chromosome. The first complete telomere-to-telomere sequence of a human autosomal chromosome, chromosome 8, followed a year later. The complete human genome (without Y chromosome) was published in 2021, while with Y chromosome in January 2022.
In 2023, a draft human pangenome reference was published. It is based on 47 genomes from persons of varied ethnicity. Plans are underway for an improved reference capturing still more biodiversity from a still wider sample.
The total length of the human reference genome does not represent the sequence of any specific individual. The genome is organized into 22 paired chromosomes, termed autosomes, plus the 23rd pair of sex chromosomes (XX) in the female and (XY) in the male. The haploid genome is 3 054 815 472 base pairs, when the X chromosome is included, and 2 963 015 935 base pairs when the Y chromosome
is substituted for the X chromosome. These chromosomes are all large
linear DNA molecules contained within the cell nucleus. The genome also
includes the mitochondrial DNA, a comparatively small circular molecule present in multiple copies in each mitochondrion.
Original analysis published in the Ensembl database at the European Bioinformatics Institute (EBI) and Wellcome Trust Sanger Institute.
Chromosome lengths estimated by multiplying the number of base pairs
(of older reference genome, not CHM13v2.0) by 0.34 nanometers (distance
between base pairs in the most common structure of the DNA double helix;
a recent estimate of human chromosome lengths based on updated data
reports 205.00 cm for the diploid male genome and 208.23 cm for female,
corresponding to weights of 6.41 and 6.51 picograms (pg), respectively). Number of proteins is based on the number of initial precursor mRNA transcripts, and does not include products of alternative pre-mRNA splicing, or modifications to protein structure that occur after translation.
Variations
are unique DNA sequence differences that have been identified in the
individual human genome sequences analyzed by Ensembl as of December
2016. The number of identified variations is expected to increase as
further personal genomes
are sequenced and analyzed. In addition to the gene content shown in
this table, a large number of non-expressed functional sequences have
been identified throughout the human genome (see below). Links open
windows to the reference chromosome sequences in the EBI genome browser.
Small non-coding RNAs are RNAs of as many as 200 bases that do not have protein-coding potential. These include: microRNAs, or miRNAs (post-transcriptional regulators of gene expression), small nuclear RNAs, or snRNAs (the RNA components of spliceosomes), and small nucleolar RNAs, or snoRNA (involved in guiding chemical modifications to other RNA molecules). Long non-coding RNAs are RNA molecules longer than 200 bases that do not have protein-coding potential. These include: ribosomal RNAs, or rRNAs (the RNA components of ribosomes), and a variety of other long RNAs that are involved in regulation of gene expression, epigenetic modifications of DNA nucleotides and histone
proteins, and regulation of the activity of protein-coding genes. Small
discrepancies between total-small-ncRNA numbers and the numbers of
specific types of small ncNRAs result from the former values being
sourced from Ensembl release 87 and the latter from Ensembl release 68.
The number of genes in the human genome is not entirely clear because the function of numerous transcripts remains unclear. This is especially true for non-coding RNA.
The number of protein-coding genes is better known but there are still
on the order of 1,400 questionable genes which may or may not encode
functional proteins, usually encoded by short open reading frames.
Discrepancies in human gene number estimates among different databases, as of July 2018
Gencode
Ensembl
Refseq
CHESS
protein-coding genes
19,901
20,376
20,345
21,306
lncRNA genes
15,779
14,720
17,712
18,484
antisense RNA
5501
28
2694
miscellaneous RNA
2213
2222
13,899
4347
Pseudogenes
14,723
1740
15,952
total transcripts
203,835
203,903
154,484
328,827
Number of genes (orange) and base pairs (green, in millions) on each chromosome
Information content
The haploid human genome (23 chromosomes)
is about 3 billion base pairs long and in 2018 was said to contain at
least 46,831 genes. In 2022 the number increased again to 63,494 genes.
The increase from the previously accepted number of around 20,000 is due
to the difficulty of defining what a gene is. It is widely agreed that
there are about 20,000 protein-coding genes, with some papers stating
exact figures of 21,306. The higher figures include non-protein coding
RNA-producing genes that perform other cell functions.
Since every base pair can be coded by 2 bits, this is about 750 megabytes of data. An individual somatic (diploid)
cell contains twice this amount, that is, about 6 billion base pairs.
Males have fewer than females because the Y chromosome is about 62
million base pairs whereas the X is about 154 million. Since individual
genomes vary in sequence by less than 1% from each other, the variations
of a given human's genome from a common reference can be losslessly compressed to roughly 4 megabytes.
The entropy rate
of the genome differs significantly between coding and non-coding
sequences. It is close to the maximum of 2 bits per base pair for the
coding sequences (about 45 million base pairs), but less for the
non-coding parts. It ranges between 1.5 and 1.9 bits per base pair for
the individual chromosome, except for the Y chromosome, which has an
entropy rate below 0.9 bits per base pair.
The content of the human genome is commonly divided into coding and noncoding DNA sequences. Coding DNA is defined as those sequences that can be transcribed into mRNA and translated into proteins during the human life cycle; these sequences occupy only a small fraction of the genome (<2%). Noncoding DNA is made up of all of those sequences (approx. 98% of the genome) that are not used to encode proteins.
Some noncoding DNA contains genes for RNA molecules with important biological functions (noncoding RNA, for example ribosomal RNA and transfer RNA).
The exploration of the function and evolutionary origin of noncoding
DNA is an important goal of contemporary genome research, including the ENCODE
(Encyclopedia of DNA Elements) project, which aims to survey the entire
human genome, using a variety of experimental tools whose results are
indicative of molecular activity. It is however disputed whether
molecular activity (transcription of DNA into RNA) alone implies that
the RNA produced has a meaningful biological function, since experiments
have shown that random nonfunctional DNA will also reproducibly recruit
transcription factors resulting in transcription into nonfunctional
RNA.
There is no consensus on what constitutes a "functional" element
in the genome since geneticists, evolutionary biologists, and molecular
biologists employ different definitions and methods.Due to the ambiguity in the terminology, different schools of thought have emerged.
In evolutionary definitions, "functional" DNA, whether it is coding or
non-coding, contributes to the fitness of the organism, and therefore is
maintained by negative evolutionary pressure
whereas "non-functional" DNA has no benefit to the organism and
therefore is under neutral selective pressure. This type of DNA has been
described as junk DNA
In genetic definitions, "functional" DNA is related to how DNA segments
manifest by phenotype and "nonfunctional" is related to
loss-of-function effects on the organism.
In biochemical definitions, "functional" DNA relates to DNA sequences
that specify molecular products (e.g. noncoding RNAs) and biochemical
activities with mechanistic roles in gene or genome regulation (i.e. DNA
sequences that impact cellular level activity such as cell type,
condition, and molecular processes).
There is no consensus in the literature on the amount of functional DNA
since, depending on how "function" is understood, ranges have been
estimated from up to 90% of the human genome is likely nonfunctional DNA
(junk DNA) to up to 80% of the genome is likely functional. It is also possible that junk DNA may acquire a function in the future and therefore may play a role in evolution, but this is likely to occur only very rarely. Finally DNA that is deliterious to the organism and is under negative selective pressure is called garbage DNA.
Because non-coding DNA greatly outnumbers coding DNA, the concept
of the sequenced genome has become a more focused analytical concept
than the classical concept of the DNA-coding gene.
Human
genes categorized by function of the transcribed proteins, given both
as number of encoding genes and percentage of all genes
Protein-coding sequences represent the most widely studied and best
understood component of the human genome. These sequences ultimately
lead to the production of all human proteins, although several biological processes (e.g. DNA rearrangements and alternative pre-mRNA splicing)
can lead to the production of many more unique proteins than the number
of protein-coding genes. The complete modular protein-coding capacity
of the genome is contained within the exome, and consists of DNA sequences encoded by exons
that can be translated into proteins. Because of its biological
importance, and the fact that it constitutes less than 2% of the genome,
sequencing of the exome was the first major milepost of the Human
Genome Project.
Number of protein-coding genes. About 20,000 human proteins have been annotated in databases such as Uniprot. Historically, estimates for the number of protein genes have varied widely, ranging up to 2,000,000 in the late 1960s, but several researchers pointed out in the early 1970s that the estimated mutational load
from deleterious mutations placed an upper limit of approximately
40,000 for the total number of functional loci (this includes
protein-coding and functional non-coding genes). The number of human protein-coding genes is not significantly larger than that of many less complex organisms, such as the roundworm and the fruit fly. This difference may result from the extensive use of alternative pre-mRNA splicing
in humans, which provides the ability to build a very large number of
modular proteins through the selective incorporation of exons.
Protein-coding capacity per chromosome. Protein-coding
genes are distributed unevenly across the chromosomes, ranging from a
few dozen to more than 2000, with an especially high gene density
within chromosomes 1, 11, and 19. Each chromosome contains various
gene-rich and gene-poor regions, which may be correlated with chromosome bands and GC-content. The significance of these nonrandom patterns of gene density is not well understood.
Size of protein-coding genes. The size of protein-coding genes within the human genome shows enormous variability. For example, the gene for histone H1a
(HIST1HIA) is relatively small and simple, lacking introns and encoding
an 781 nucleotide-long mRNA that produces a 215 amino acid protein from
its 648 nucleotide open reading frame. Dystrophin (DMD) was the largest protein-coding gene in the 2001 human reference genome, spanning a total of 2.2 million nucleotides, while more recent systematic meta-analysis of updated human genome data identified an even larger protein-coding gene, RBFOX1 (RNA binding protein, fox-1 homolog 1), spanning a total of 2.47 million nucleotides. Titin (TTN) has the longest coding sequence (114,414 nucleotides), the largest number of exons (363),
and the longest single exon (17,106 nucleotides). As estimated based on
a curated set of protein-coding genes over the whole genome, the median
size is 26,288 nucleotides (mean = 66,577), the median exon size, 133
nucleotides (mean = 309), the median number of exons, 8 (mean = 11), and
the median encoded protein is 425 amino acids (mean = 553) in length.
Noncoding DNA is defined as all of the DNA sequences within a genome
that are not found within protein-coding exons, and so are never
represented within the amino acid sequence of expressed proteins. By
this definition, more than 98% of the human genomes is composed of
ncDNA.
Numerous classes of noncoding DNA have been identified, including
genes for noncoding RNA (e.g. tRNA and rRNA), pseudogenes, introns,
untranslated regions of mRNA, regulatory DNA sequences, repetitive DNA
sequences, and sequences related to mobile genetic elements.
Numerous sequences that are included within genes are also
defined as noncoding DNA. These include genes for noncoding RNA (e.g.
tRNA, rRNA), and untranslated components of protein-coding genes (e.g.
introns, and 5' and 3' untranslated regions of mRNA).
Protein-coding sequences (specifically, coding exons) constitute less than 1.5% of the human genome. In addition, about 26% of the human genome is introns.
Aside from genes (exons and introns) and known regulatory sequences
(8–20%), the human genome contains regions of noncoding DNA. The exact
amount of noncoding DNA that plays a role in cell physiology has been
hotly debated. An analysis by the ENCODE
project indicates that 80% of the entire human genome is either
transcribed, binds to regulatory proteins, or is associated with some
other biochemical activity.
It however remains controversial whether all of this biochemical
activity contributes to cell physiology, or whether a substantial
portion of this is the result of transcriptional and biochemical noise,
which must be actively filtered out by the organism. Excluding protein-coding sequences, introns, and regulatory regions, much of the non-coding DNA is composed of:
Many DNA sequences that do not play a role in gene expression have important biological functions. Comparative genomics studies indicate that about 5% of the genome contains sequences of noncoding DNA that are highly conserved, sometimes on time-scales representing hundreds of millions of years, implying that these noncoding regions are under strong evolutionary pressure and purifying selection.
Many of these sequences regulate the structure of chromosomes by limiting the regions of heterochromatin formation and regulating structural features of the chromosomes, such as the telomeres and centromeres. Other noncoding regions serve as origins of DNA replication.
Finally several regions are transcribed into functional noncoding RNA
that regulate the expression of protein-coding genes (for example), mRNA translation and stability (see miRNA), chromatin structure (including histone modifications, for example), DNA methylation (for example), DNA recombination (for example), and cross-regulate other noncoding RNAs (for example).
It is also likely that many transcribed noncoding regions do not serve
any role and that this transcription is the product of non-specific RNA Polymerase activity.
Pseudogenes are inactive copies of protein-coding genes, often generated by gene duplication,
that have become nonfunctional through the accumulation of inactivating
mutations. The number of pseudogenes in the human genome is on the
order of 13,000,
and in some chromosomes is nearly the same as the number of functional
protein-coding genes. Gene duplication is a major mechanism through
which new genetic material is generated during molecular evolution.
For example, the olfactory receptor
gene family is one of the best-documented examples of pseudogenes in
the human genome. More than 60 percent of the genes in this family are
non-functional pseudogenes in humans. By comparison, only 20 percent of
genes in the mouse olfactory receptor gene family are pseudogenes.
Research suggests that this is a species-specific characteristic, as the
most closely related primates all have proportionally fewer
pseudogenes. This genetic discovery helps to explain the less acute
sense of smell in humans relative to other mammals.
Noncoding RNA molecules play many essential roles in cells, especially in the many reactions of protein synthesis and RNA processing. Noncoding RNA include tRNA, ribosomal RNA, microRNA, snRNA and other non-coding RNA genes including about 60,000 long non-coding RNAs (lncRNAs).
Although the number of reported lncRNA genes continues to rise and the
exact number in the human genome is yet to be defined, many of them are
argued to be non-functional.
Many ncRNAs are critical elements in gene regulation and
expression. Noncoding RNA also contributes to epigenetics,
transcription, RNA splicing, and the translational machinery. The role
of RNA in genetic regulation and disease offers a new potential level of
unexplored genomic complexity.
Introns and untranslated regions of mRNA
In
addition to the ncRNA molecules that are encoded by discrete genes, the
initial transcripts of protein coding genes usually contain extensive
noncoding sequences, in the form of introns, 5'-untranslated regions (5'-UTR), and 3'-untranslated regions
(3'-UTR). Within most protein-coding genes of the human genome, the
length of intron sequences is 10- to 100-times the length of exon
sequences.
Regulatory DNA sequences
The human genome has many different regulatory sequences which are crucial to controlling gene expression. Conservative estimates indicate that these sequences make up 8% of the genome, however extrapolations from the ENCODE project give that 20-40%
of the genome is gene regulatory sequence. Some types of non-coding DNA
are genetic "switches" that do not encode proteins, but do regulate
when and where genes are expressed (called enhancers).
Regulatory sequences have been known since the late 1960s. The first identification of regulatory sequences in the human genome relied on recombinant DNA technology.
Later with the advent of genomic sequencing, the identification of
these sequences could be inferred by evolutionary conservation. The
evolutionary branch between the primates and mouse, for example, occurred 70–90 million years ago. So computer comparisons of gene sequences that identify conserved non-coding sequences will be an indication of their importance in duties such as gene regulation.
Other genomes have been sequenced with the same intention of aiding conservation-guided methods, for exampled the pufferfish genome. However, regulatory sequences disappear and re-evolve during evolution at a high rate.
As of 2012, the efforts have shifted toward finding interactions between DNA and regulatory proteins by the technique ChIP-Seq, or gaps where the DNA is not packaged by histones (DNase hypersensitive sites), both of which tell where there are active regulatory sequences in the investigated cell type.
About 8% of the human genome consists of tandem DNA arrays or
tandem repeats, low complexity repeat sequences that have multiple
adjacent copies (e.g. "CAGCAGCAG...").
The tandem sequences may be of variable lengths, from two nucleotides
to tens of nucleotides. These sequences are highly variable, even among
closely related individuals, and so are used for genealogical DNA testing and forensic DNA analysis.
Repeated sequences of fewer than ten nucleotides (e.g. the dinucleotide repeat (AC)n)
are termed microsatellite sequences. Among the microsatellite
sequences, trinucleotide repeats are of particular importance, as
sometimes occur within coding regions
of genes for proteins and may lead to genetic disorders. For example,
Huntington's disease results from an expansion of the trinucleotide
repeat (CAG)n within the Huntingtin gene on human chromosome 4. Telomeres (the ends of linear chromosomes) end with a microsatellite hexanucleotide repeat of the sequence (TTAGGG)n.
Tandem repeats of longer sequences (arrays of repeated sequences 10–60 nucleotides long) are termed minisatellites.
Mobile genetic elements (transposons) and their relics
Transposable genetic elements,
DNA sequences that can replicate and insert copies of themselves at
other locations within a host genome, are an abundant component in the
human genome. The most abundant transposon lineage, Alu, has about 50,000 active copies, and can be inserted into intragenic and intergenic regions. One other lineage, LINE-1, has about 100 active copies per genome (the number varies between people). Together with non-functional relics of old transposons, they account for over half of total human DNA.
Sometimes called "jumping genes", transposons have played a major role
in sculpting the human genome. Some of these sequences represent endogenous retroviruses,
DNA copies of viral sequences that have become permanently integrated
into the genome and are now passed on to succeeding generations.
With the exception of identical twins, all humans show significant variation in genomic DNA sequences. The human reference genome (HRG) is used as a standard sequence reference.
There are several important points concerning the human reference genome:
The HRG is a haploid sequence. Each chromosome is represented once.
The HRG is a composite sequence, and does not correspond to any actual human individual.
The HRG is periodically updated to correct errors, ambiguities, and unknown "gaps".
The HRG in no way represents an "ideal" or "perfect" human
individual. It is simply a standardized representation or model that is
used for comparative purposes.
The Genome Reference Consortium is responsible for updating the HRG. Version 38 was released in December 2013.
Measuring human genetic variation
Most studies of human genetic variation have focused on single-nucleotide polymorphisms
(SNPs), which are substitutions in individual bases along a chromosome.
Most analyses estimate that SNPs occur 1 in 1000 base pairs, on
average, in the euchromatic
human genome, although they do not occur at a uniform density. Thus
follows the popular statement that "we are all, regardless of race, genetically 99.9% the same",
although this would be somewhat qualified by most geneticists. For
example, a much larger fraction of the genome is now thought to be
involved in copy number variation. A large-scale collaborative effort to catalog SNP variations in the human genome is being undertaken by the International HapMap Project.
The genomic loci and length of certain types of small repetitive sequences are highly variable from person to person, which is the basis of DNA fingerprinting and DNA paternity testing technologies. The heterochromatic
portions of the human genome, which total several hundred million base
pairs, are also thought to be quite variable within the human population
(they are so repetitive and so long that they cannot be accurately
sequenced with current technology). These regions contain few genes, and
it is unclear whether any significant phenotypic effect results from typical variation in repeats or heterochromatin.
Most gross genomic mutations in gamete
germ cells probably result in inviable embryos; however, a number of
human diseases are related to large-scale genomic abnormalities. Down syndrome, Turner Syndrome, and a number of other diseases result from nondisjunction of entire chromosomes. Cancer cells frequently have aneuploidy of chromosomes and chromosome arms, although a cause and effect relationship between aneuploidy and cancer has not been established.
Mapping human genomic variation
Whereas
a genome sequence lists the order of every DNA base in a genome, a
genome map identifies the landmarks. A genome map is less detailed than a
genome sequence and aids in navigating around the genome.
An example of a variation map is the HapMap being developed by the International HapMap Project. The HapMap is a haplotype map of the human genome, "which will describe the common patterns of human DNA sequence variation." It catalogs the patterns of small-scale variations in the genome that involve single DNA letters, or bases.
Researchers published the first sequence-based map of large-scale structural variation across the human genome in the journal Nature in May 2008.
Large-scale structural variations are differences in the genome among
people that range from a few thousand to a few million DNA bases; some
are gains or losses of stretches of genome sequence and others appear as
re-arrangements of stretches of sequence. These variations include differences in the number of copies individuals have of a particular gene, deletions, translocations and inversions.
Structural variation
Structural variation refers to genetic variants that affect larger segments of the human genome, as opposed to point mutations.
Often, structural variants (SVs) are defined as variants of 50 base
pairs (bp) or greater, such as deletions, duplications, insertions,
inversions and other rearrangements. About 90% of structural variants
are noncoding deletions but most individuals have more than a thousand
such deletions; the size of deletions ranges from dozens of base pairs
to tens of thousands of bp. On average, individuals carry ~3 rare structural variants that alter coding regions, e.g. delete exons.
About 2% of individuals carry ultra-rare megabase-scale structural
variants, especially rearrangements. That is, millions of base pairs may
be inverted within a chromosome; ultra-rare means that they are only
found in individuals or their family members and thus have arisen very
recently.
SNP frequency across the human genome
Single-nucleotide polymorphisms (SNPs) do not occur homogeneously across
the human genome. In fact, there is enormous diversity in SNP
frequency between genes, reflecting different selective pressures on
each gene as well as different mutation and recombination rates across
the genome. However, studies on SNPs are biased towards coding regions,
the data generated from them are unlikely to reflect the overall
distribution of SNPs throughout the genome. Therefore, the SNP Consortium
protocol was designed to identify SNPs with no bias towards coding
regions and the Consortium's 100,000 SNPs generally reflect sequence
diversity across the human chromosomes. The SNP Consortium aims to expand the number of SNPs identified across the genome to 300 000 by the end of the first quarter of 2001.
TSC SNP distribution along the long arm of chromosome 22 (from https://web.archive.org/web/20130903043223/http://snp.cshl.org/
). Each column represents a 1 Mb interval; the approximate cytogenetic
position is given on the x-axis. Clear peaks and troughs of SNP density
can be seen, possibly reflecting different rates of mutation,
recombination and selection.
Changes in non-coding sequence and synonymous changes in coding sequence
are generally more common than non-synonymous changes, reflecting
greater selective pressure reducing diversity at positions dictating
amino acid identity. Transitional changes are more common than
transversions, with CpG dinucleotides showing the highest mutation rate,
presumably due to deamination.
A personal genome sequence is a (nearly) complete sequence of the chemical base pairs that make up the DNA of a single person. Because medical treatments have different effects on different people due to genetic variations such as single-nucleotide polymorphisms (SNPs), the analysis of personal genomes may lead to personalized medical treatment based on individual genotypes.
The first personal genome sequence to be determined was that of Craig Venter
in 2007. Personal genomes had not been sequenced in the public Human
Genome Project to protect the identity of volunteers who provided DNA
samples. That sequence was derived from the DNA of several volunteers
from a diverse population. However, early in the Venter-led Celera Genomics
genome sequencing effort the decision was made to switch from
sequencing a composite sample to using DNA from a single individual,
later revealed to have been Venter himself. Thus the Celera human genome
sequence released in 2000 was largely that of one man. Subsequent
replacement of the early composite-derived data and determination of the
diploid sequence, representing both sets of chromosomes, rather than a haploid sequence originally reported, allowed the release of the first personal genome. In April 2008, that of James Watson
was also completed. In 2009, Stephen Quake published his own genome
sequence derived from a sequencer of his own design, the Heliscope. A Stanford team led by Euan Ashley
published a framework for the medical interpretation of human genomes
implemented on Quake's genome and made whole genome-informed medical
decisions for the first time.
That team further extended the approach to the West family, the first
family sequenced as part of Illumina's Personal Genome Sequencing
program. Since then hundreds of personal genome sequences have been released, including those of Desmond Tutu, and of a Paleo-Eskimo. In 2012, the whole genome sequences of two family trios among 1092 genomes was made public. In November 2013, a Spanish family made four personal exome datasets (about 1% of the genome) publicly available under a Creative Commons public domain license. The Personal Genome Project (started in 2005) is among the few to make both genome sequences and corresponding medical phenotypes publicly available.
The sequencing of individual genomes further unveiled levels of
genetic complexity that had not been appreciated before. Personal
genomics helped reveal the significant level of diversity in the human
genome attributed not only to SNPs but structural variations as well.
However, the application of such knowledge to the treatment of disease
and in the medical field is only in its very beginnings. Exome sequencing
has become increasingly popular as a tool to aid in diagnosis of
genetic disease because the exome contributes only 1% of the genomic
sequence but accounts for roughly 85% of mutations that contribute
significantly to disease.
Human knockouts
In humans, gene knockouts naturally occur as heterozygous or homozygousloss-of-function gene knockouts. These knockouts are often difficult to distinguish, especially within heterogeneous genetic backgrounds. They are also difficult to find as they occur in low frequencies.
Populations
with a high level of parental-relatedness result in a larger number of
homozygous gene knockouts as compared to outbred populations.
Populations with high rates of consanguinity,
such as countries with high rates of first-cousin marriages, display
the highest frequencies of homozygous gene knockouts. Such populations
include Pakistan, Iceland, and Amish populations. These populations with
a high level of parental-relatedness have been subjects of human knock
out research which has helped to determine the function of specific
genes in humans. By distinguishing specific knockouts, researchers are
able to use phenotypic analyses of these individuals to help
characterize the gene that has been knocked out.
A
pedigree displaying a first-cousin mating (carriers both carrying
heterozygous knockouts mating as marked by double line) leading to
offspring possessing a homozygous gene knockout
Knockouts in specific genes can cause genetic diseases, potentially
have beneficial effects, or even result in no phenotypic effect at all.
However, determining a knockout's phenotypic effect and in humans can be
challenging. Challenges to characterizing and clinically interpreting
knockouts include difficulty calling of DNA variants, determining
disruption of protein function (annotation), and considering the amount
of influence mosaicism has on the phenotype.
One major study that investigated human knockouts is the Pakistan
Risk of Myocardial Infarction study. It was found that individuals
possessing a heterozygous loss-of-function gene knockout for the APOC3
gene had lower triglycerides in the blood after consuming a high fat
meal as compared to individuals without the mutation. However,
individuals possessing homozygous loss-of-function gene knockouts of the
APOC3 gene displayed the lowest level of triglycerides in the blood
after the fat load test, as they produce no functional APOC3 protein.
Most aspects of human biology involve both genetic (inherited) and
non-genetic (environmental) factors. Some inherited variation influences
aspects of our biology that are not medical in nature (height, eye
color, ability to taste or smell certain compounds, etc.). Moreover,
some genetic disorders only cause disease in combination with the
appropriate environmental factors (such as diet). With these caveats,
genetic disorders may be described as clinically defined diseases caused
by genomic DNA sequence variation. In the most straightforward cases,
the disorder can be associated with variation in a single gene. For
example, cystic fibrosis
is caused by mutations in the CFTR gene and is the most common
recessive disorder in caucasian populations with over 1,300 different
mutations known.
Disease-causing mutations in specific genes are usually severe in
terms of gene function and are fortunately rare, thus genetic disorders
are similarly individually rare. However, since there are many genes
that can vary to cause genetic disorders, in aggregate they constitute a
significant component of known medical conditions, especially in
pediatric medicine. Molecularly characterized genetic disorders are
those for which the underlying causal gene has been identified.
Currently there are approximately 2,200 such disorders annotated in the OMIM database.
Studies of genetic disorders are often performed by means of
family-based studies. In some instances, population based approaches are
employed, particularly in the case of so-called founder populations
such as those in Finland, French-Canada, Utah, Sardinia, etc. Diagnosis
and treatment of genetic disorders are usually performed by a geneticist-physician trained in clinical/medical genetics. The results of the Human Genome Project are likely to provide increased availability of genetic testing for gene-related disorders, and eventually improved treatment. Parents can be screened for hereditary conditions and counselled on the consequences, the probability of inheritance, and how to avoid or ameliorate it in their offspring.
There are many different kinds of DNA sequence variation, ranging
from complete extra or missing chromosomes down to single nucleotide
changes. It is generally presumed that much naturally occurring genetic
variation in human populations is phenotypically neutral, i.e., has
little or no detectable effect on the physiology of the individual
(although there may be fractional differences in fitness defined over
evolutionary time frames). Genetic disorders can be caused by any or all
known types of sequence variation. To molecularly characterize a new
genetic disorder, it is necessary to establish a causal link between a
particular genomic sequence variant and the clinical disease under
investigation. Such studies constitute the realm of human molecular
genetics.
With the advent of the Human Genome and International HapMap Project,
it has become feasible to explore subtle genetic influences on many
common disease conditions such as diabetes, asthma, migraine,
schizophrenia, etc. Although some causal links have been made between
genomic sequence variants in particular genes and some of these
diseases, often with much publicity in the general media, these are
usually not considered to be genetic disorders per se as their
causes are complex, involving many different genetic and environmental
factors. Thus there may be disagreement in particular cases whether a
specific medical condition should be termed a genetic disorder.
Additional genetic disorders of mention are Kallman syndrome and Pfeiffer syndrome (gene FGFR1), Fuchs corneal dystrophy (gene TCF4), Hirschsprung's disease
(genes RET and FECH), Bardet-Biedl syndrome 1 (genes CCDC28B and BBS1),
Bardet-Biedl syndrome 10 (gene BBS10), and facioscapulohumeral muscular
dystrophy type 2 (genes D4Z4 and SMCHD1).
Genome sequencing is now able to narrow the genome down to
specific locations to more accurately find mutations that will result in
a genetic disorder. Copy number variants (CNVs) and single nucleotide variants
(SNVs) are also able to be detected at the same time as genome
sequencing with newer sequencing procedures available, called Next
Generation Sequencing (NGS).
This only analyzes a small portion of the genome, around 1–2%. The
results of this sequencing can be used for clinical diagnosis of a
genetic condition, including Usher syndrome, retinal disease, hearing impairments, diabetes, epilepsy, Leigh disease, hereditary cancers, neuromuscular diseases, primary immunodeficiencies, severe combined immunodeficiency (SCID), and diseases of the mitochondria.
NGS can also be used to identify carriers of diseases before
conception. The diseases that can be detected in this sequencing include
Tay-Sachs disease, Bloom syndrome, Gaucher disease, Canavan disease, familial dysautonomia, cystic fibrosis, spinal muscular atrophy, and fragile-X syndrome.
The Next Genome Sequencing can be narrowed down to specifically look
for diseases more prevalent in certain ethnic populations.
Prevalence and associated gene/chromosome for some human genetic disorders
Comparative genomics
studies of mammalian genomes suggest that approximately 5% of the human
genome has been conserved by evolution since the divergence of extant
lineages approximately 200 million years ago, containing the vast
majority of genes. The published chimpanzee genome differs from that of the human genome by 1.23% in direct sequence comparisons.
Around 20% of this figure is accounted for by variation within each
species, leaving only ~1.06% consistent sequence divergence between
humans and chimps at shared genes.
This nucleotide by nucleotide difference is dwarfed, however, by the
portion of each genome that is not shared, including around 6% of
functional genes that are unique to either humans or chimps.
In other words, the considerable observable differences between
humans and chimps may be due as much or more to genome level variation
in the number, function and expression of genes rather than DNA sequence
changes in shared genes. Indeed, even within humans, there has been
found to be a previously unappreciated amount of copy number variation
(CNV) which can make up as much as 5–15% of the human genome. In other
words, between humans, there could be +/- 500,000,000 base pairs of DNA,
some being active genes, others inactivated, or active at different
levels. The full significance of this finding remains to be seen. On
average, a typical human protein-coding gene differs from its chimpanzee
ortholog by only two amino acid
substitutions; nearly one third of human genes have exactly the same
protein translation as their chimpanzee orthologs. A major difference
between the two genomes is human chromosome 2, which is equivalent to a fusion product of chimpanzee chromosomes 12 and 13. (later renamed to chromosomes 2A and 2B, respectively).
Humans have undergone an extraordinary loss of olfactory receptor genes during our recent evolution, which explains our relatively crude sense of smell compared to most other mammals. Evolutionary evidence suggests that the emergence of color vision in humans and several other primate species has diminished the need for the sense of smell.
The human mitochondrial DNA is of tremendous interest to geneticists, since it undoubtedly plays a role in mitochondrial disease.
It also sheds light on human evolution; for example, analysis of
variation in the human mitochondrial genome has led to the postulation
of a recent common ancestor for all humans on the maternal line of
descent (see Mitochondrial Eve).
Due to the lack of a system for checking for copying errors,
mitochondrial DNA (mtDNA) has a more rapid rate of variation than
nuclear DNA. This 20-fold higher mutation rate allows mtDNA to be used
for more accurate tracing of maternal ancestry. Studies of mtDNA in populations have allowed ancient migration paths to be traced, such as the migration of Native Americans from Siberia or Polynesians from southeastern Asia. It has also been used to show that there is no trace of Neanderthal DNA in the European gene mixture inherited through purely maternal lineage.
Due to the restrictive all or none manner of mtDNA inheritance, this
result (no trace of Neanderthal mtDNA) would be likely unless there were
a large percentage of Neanderthal ancestry, or there was strong
positive selection for that mtDNA. For example, going back 5
generations, only 1 of a person's 32 ancestors contributed to that
person's mtDNA, so if one of these 32 was pure Neanderthal an expected
~3% of that person's autosomal DNA would be of Neanderthal origin, yet
they would have a ~97% chance of having no trace of Neanderthal mtDNA.
Epigenetics describes a variety of features of the human genome that transcend its primary DNA sequence, such as chromatin packaging, histone modifications and DNA methylation,
and which are important in regulating gene expression, genome
replication and other cellular processes. Epigenetic markers strengthen
and weaken transcription of certain genes but do not affect the actual
sequence of DNA nucleotides. DNA methylation is a major form of
epigenetic control over gene expression and one of the most highly
studied topics in epigenetics. During development, the human DNA
methylation profile experiences dramatic changes. In early germ line
cells, the genome has very low methylation levels. These low levels
generally describe active genes. As development progresses, parental
imprinting tags lead to increased methylation activity.
Epigenetic patterns can be identified between tissues within an
individual as well as between individuals themselves. Identical genes
that have differences only in their epigenetic state are called epialleles.
Epialleles can be placed into three categories: those directly
determined by an individual's genotype, those influenced by genotype,
and those entirely independent of genotype. The epigenome is also
influenced significantly by environmental factors. Diet, toxins, and
hormones impact the epigenetic state. Studies in dietary manipulation
have demonstrated that methyl-deficient diets are associated with
hypomethylation of the epigenome. Such studies establish epigenetics as
an important interface between the environment and the genome.
