Сравнительная геномикаПолиморфизм генома человека

ФББ, 4 курс

Василий Евгеньевич Раменский, Институт молекулярной биологии РАН

People are different…

…caccagctcctgtgGggggaggccctgct… …caccagctcctgtgGggggaggccctgct… …caccagctcctgtgGggggaggccctgct… …caccagctcctgtgCggggaggccctgct… …caccagctcctgtgCggggaggccctgct…

…and so are their genomes

Определение

SNP (single nucleotide polymorphism): существование в популяции на одной и той же позиции геномной ДНК двух нуклеотидных вариантов с частотой более редкого варианта (аллеля) ≥1%

5’---------------A---------------3’ |||||||||||||||||||||||||||||||3’---------------T---------------5’

5’---------------G---------------3’ |||||||||||||||||||||||||||||||3’---------------C---------------5’

Na

Ng

Na+Ng = N, Na/N ≥0.01, Ng/N ≥0.01

Комментарии к определению

•речь идет о сравнении последовательностей одного биол. вида

•слово «полиморфизм» не имеет в русском языке

множественного числа (Н.Ляпунова, личное сообщение)

•в обыденной речи под «полиморфизмом» чаще всего

подразумевают именно нуклеотид (т.е. используют его как

синоним слова «мутация»)

•определение подразумевает достоверное измерение частот в

популяции(-ях), что в текущей практике пока редкость

Типы полиморфизма в геноме

* однонуклеотидный (SNP)

* короткая вставка/делеция

* микросателлитный повтор различной длины (VNTR,

variable number tandem repeat)

* вставка объекта

* множественный нуклеотидный (MNP)

Некоторые свойства SNPs

• Comprise the ~90% of human genetic variation

• Occur with an average density ~1/1000 bp

• Transition C↔T(G↔A) occurs at ~2/3 of all cases, three

transversions C↔A (G↔T), C↔G(G↔C), T↔A(A↔T) in

~1/6 of all cases each

• Most of them (~85%) are common to all populations

(with differing allele frequencies)

Why SNPs are important?

• Convenient genetic markers

• Responsible for existence of various phenotypes,

with primary interest in disease ones

• Pharmacogenomics: individual response to drugs

• Clues to understand human evolution

SNP в геноме человека

Build Date # rs’s, x106

10? Feb. 01. . . . . . . . . .1.42

106 Aug. 02. . . . . . . . . .2.81

110 Jan. 03. . . . . . . . . . 3.05

119 Jan. 04. . . . . . . . . . 7.23

124 Jan. 05 . . . . . . . . . .10.0

dbSNP build statistics

Estimates of SNP density in the human genome

• Li and Sadler (1991), Genetics, ~1/1000 bp

• Zhao et al., (2003), Gene: ~1/1200 bp

• dbSNP, build 124 (2005): ~1/300 bp (?)

Классификация SNP по положению в геноме

1. гены

1.1 UTR

1.2 экзоны (cSNP)

1.2.1 синонимичные(sSNP)

1.2.2 несинонимичные (nsSNP)

1.3 интроны

1.4 сайты сплайсинга

2. регуляторные участки генов (rSNP)

3. межгенные участки

Synonymous vs. non-synonymous SNPs:

…CAC CAG CTC CTG TGG GGG GAG GCC CTG CT…

…CAC CAG CTC CTG TGC GGG GAG GCT CTG CT…

HGVBase ID: SNP000003023 G C Hypothetical SNP: C T

… H Q L L W G E A L …

… H Q L L C G E A L …

Example: Lysosomal alpha-glucosidase precursor (SwissProt P10253)

nsSNP Trp746Cys sSNP Ala749Ala

Summary of Annotation on human Genome Build 33 dbSNP Build 124 :

FUNCTION CLASS CODE

SNP COUNTGENE

COUNT

FUNCTIONAL

CLASSIFICATION

1 338787 26210 Locus region

3 39214 14342Allele synonymous to contig nucleotide

4 50772 15710Allele nonsynonymous to contig nucleotide

5 546965 17898 untranslated region

6 2925773 19332 intron

7 832 769 splice site

8 89554 18655 Allele is same as contig nucleotide

9 7111 1006 Coding: synonymy unknown

Упражнение

В одной базе ~11,000 nsSNPs в ~6,000 белков. В другой базе

~47,000 последовательностей белков общей длиной

~19.5x106 остатков. Оценить

(а) среднюю длину белка

(б) среднее число nsSNP в одном белке

(в) среднее число nsSNP на единицу длины белка

Жизненный цикл SNP (по Miller&Kwok, 2001)

I. Появление нового аллельного варианта путем мутации

(~100 мутаций на индивидуум)

II. «Выживание» до момента появления гомозигот по этому

аллелю

III. Медленное увеличение частоты в популяции

IV. Фиксация нового аллеля (0 vs. 100%), превращение в

between-species difference

Упражнение

Описанный выше жизненный цикл SNP занимает ~0.3 млн

лет. Предполагая, что разделение человека и шимпанзе

произошло ~5 млн лет назад, а выход H.sapiens из Африки и

разделение различных популяций ~0.1-0.2 млн лет назад,

аргументировать возможность существования (а) одинаковых

SNPs у человека и других видов, (б) «private» SNP, т.е.

локализованных в пределах одной человеческой популяции

Why polymorphisms are maintained in the population?

• Selectionists: because heterozygotes have higher fitness

• Neutralists: because all observed polymoprhisms are selectively neutral

- - - - - -- - - - - - - - - - - - - - - - - - - - - - - - - Reality: is always somewhat more complicated

Why SNPs are important?

• Convenient genetic markers

• Responsible for existence of various phenotypes,

with primary interest in disease ones

• Pharmacogenomics: individual response to drugs

• Clues to understand human evolution

nsSNPs vs. disease mutations

Disease mutations are rare (<<1%) and usually cause monogenic diseases (e.g., cystic fibrosis)

nsSNPs are frequent (>1%) and can modify risks of major common (multigenic, complex) diseases (e.g., cancer, cardiovascular disease, mental illness, autoimmune states, diabetes)

In some cases, however, it is difficult to make a distinction

Some common nsSNPs are known to affect critical structure features

Frequency of the haemochromatosis allelic variant of HLA-H protein Cys260Tyr (with destroyed disulphide

bond) is up to 6% in Northern Europe

Identifying SNPs responsible for specific phenotypes

whole genome scan – hypothesis free approach; extraordinary number of candidate SNPs

candidate gene studies – requires a priori models; nevertheless, large numbers of candidate SNPs to be tested

Both methods, however, require huge amounts of expensive experimental data and are are statistically unreliable. Therefore, in silico expertise is required

Methods for prediction of effect of nsSNPs

* Sequence-based methods: analysis of multiple alignment with homologs Ng-Henikoff [2002]

* Structure-based methods: analysis of various structural parameters Wang, Moult [2001]; Chasman, Adams [2001]

* Combined methods: sequence and structure analysis Sunyaev,Ramensky,Bork [2000, 2001, 2002]

PolyPhen: prediction of amino acid substitution effect on protein function

Data sources:

1. Sequence annotation of the query protein2. PSIC profile matrix values derived from multiple

alignment with homologous proteins3. Structural parameters and contacts of query protein

structure or its >50% homolog

Prediction: benign (neutral), damaging (deleterious)

PolyPhen query processing flowchart

INPUT:

•Sequence: …IMAGLQQTNSE…

•Position: 133

•Var1: Q

•Var2: P

•ACC/ID (if known protein): DMD_HUMAN

sequence annotation

PSIC profile scores for two amino acid variants

structural parameters and contacts

prediction rules

PREDICTION:•damaging•benign•unknown

I. Sequence annotation

Hereditary hemochromatosis protein precursor (HLA-H, Q30201)

Features checked:* bond: DISULFID, THIOLEST, THIOETH

* site: BINDING, ACT_SITE, LIPID, METAL, SITE, MOD_RES, SE_CYS

* region: TRANSMEM, SIGNAL, PROPEP

II. PSIC: profile analysis of homologous sequences

1. Align with homologous proteins with seq. ide. 30..94%

II. PSIC: profile analysis of homologous sequences

2. Calculate the profile matrix with PSIC algorithm

Profile matrix: Sa,j = ln[ pa,j / qa ], a = {1,..20}, j = {1,..N}, N = alignment length

SAsn,4 SCys,4

II. PSIC: profile analysis of homologous sequences

3. Analyse difference between profile scores for two a.a. variants:

SAsn,4 SCys,4

AsnCys: = | SAsn,4 – SCys,4 | = 1.591

III. 3D structure analysis1. Residues that are in spatial contact with a

ligand or other “critical” residues

Zen 999

residues in 5Å contact with Zen 999

Bos Taurus trypsin [PDB ID :1ql7]

III. 3D structure analysis2. Residues that form the hydrophobic core of

the protein (buried residues)

Bos Taurus trypsin [PDB ID :1ql7]

Surface residues

Buried residues

Structural parameters and contacts

Secondary structure Phi-psi dihedral angles Solvent accessible surface area, normed s.a.s.a Change in accessible surface propensity Change in residue side chain volume Contacts with heteroatoms Interchain contacts Contacts with functional sites (BINDING,

ACT_SITE, LIPID, and METAL) Region of the phi-psi map (Ramachandran map) Normalised B-factor (temperature factor)

RULES (connected with logical AND) PREDICTION

PSIC score difference :

Substitution site properties: Substitution type properties:  

arbitraryannotated as a functional* or bond formation** site

arbitrary probably damaging

not consideredin a region annotated or predicted as transmembrane

PHAT matrix difference resulting from substitution is negative

possibly damaging

0.5 arbitrary arbitrary benign

>1.0atoms are closer than 3.0Å to atoms of a ligand or residue annotated as BINDING, ACT_SITE, LIPID, METAL

arbitrary probably damaging

0.5<1.5

normed accessibility ACC15%

absolute change of accessible surface propensity is 0.75 orabsolute change of side chain volume is 60

possibly damaging

normed accessibility ACC5%

absolute change of accessible surface propensity is 1.0 or absolute change of side chain volume is 80

probably damaging

1.5<2.0 arbitrary arbitrary possibly damaging

>2.0 arbitrary arbitrary probably damaging

Control sets

all dam unknown dam/(dam+ben)

–––––––––––––––––––––––––––––––––––––––––––––

Disease mutations

Strict set 444 366 3 82.9%

Total 2,782 2,047 70 75.4%

Between species substitutions

Total 671 58 5 8.7%

PolyPhen: predictions for nsSNPs

All SNPs from HGVBase, rel.12.............................983,589

synonymous...................................9,310 (5,378 proteins)

non-synonymous..............................11,152 (6,124 proteins)

Predictions for nsSNPs:

unknown................................................1,987

benign.................................................6,317

possibly damaging......................................1,591

probably damaging......................................1,257

Prediction basis:

multiple alignment...................................2,654

sequence annotation....................................118

structure...............................................76

PolyPhen predictions for dbSNP b.121All: 9,502 unknown27,991 benign...............67.6% 7,905 possibly damaging....19.1% 5,521 probably damaging....13.3%50,919 total (44,005 unique rs’s)

With structure: 42 unknown 2,142 benign...............57.1% 531 possibly damaging....14.2% 1,076 probably damaging....28.7% 3,791 total (,167 uniqe rs’s)

[ Ivan Adzhubei, 2004 ]

PolyPhen predictions for dbSNP b.121All: Filtered: 5 seq. in multiple alignment16,813 benign...............64.2% 5,195 possibly damaging....19.8% 4,168 probably damaging....15.9%26,176 total (21,677 unique rs’s)

With structure:Filtered: 5 seq. in multiple alignment2,021 benign...............56.6% 499 possibly damaging....14.0%1,050 probably damaging....29.4%3,570 total (2,983 unique rs’s)

[ Ivan Adzhubei, 2004 ]

Hydrophobic core stability parameters are the best predictors

Ramensky et al., Nucleic Acids Res. (2002) 30:3894-90

PolyPhen http://www.bork.embl.de/PolyPhen

PolyPhen input :

Protein identifier OR sequence

Substitution position

Substitution type

PolyPhen http://www.bork.embl.de/PolyPhen

PolyPhen: nsSNPs data collection

DAMAGING nsSNPs

Transphyretin

(PDB: 1tyr, SNP000012365)

Thr118 Asn occurs at the ligand (REA) binding site

Thr 118

REA 130

DAMAGING nsSNPs

Trypsin

(PDB: 1trn, SNP000012965)

Ser142Phe results in the strong side chain volume change at a buried position

Ser 142

PolyPhen: дитя семи нянек

ЦИКЛОП ПОЛИФЕМ ПРЕДСТАВЛЯЛ СОБОЙ УНИКАЛЬНЫЙ ПОДВИД КАРЛИКОВЫХ СЛОНОВ

Известия-Наука, 18 ноября 2003

Вонзая заостренное бревно в единственный глаз свирепого циклопа Полифема, легендарный Одиссей истреблял уникальный вид карликовых слонов, обитавших на острове Сицилия. Древний миф об одноглазых человекообразных исполинах развеяли итальянские палеонтологи на научной экспозиции "Полифем в Модене".

На выставке представлены черепа, обнаруженные исследователями на Сицилии, у которых одна фронтальная глазница. С первого взгляда она очень напоминает глаз во лбу. Найденные рядом с черепами кости действительно принадлежат немаленькому млекопитающему, которое имело габариты крупного медведя. Обладатель этих останков был не циклопом, а карликовым слоном. "Глаз" во лбу - отверстие для дыхательных путей, то есть для хобота.

Polyphenism: the ability of a single genome to produce two or more alternative morphologies within a single population in response to an environmental cue (such as temperature, photoperiod, or nutrition). [Dr. Ehab Abouheif, McGill University, Montréal Québec]

The seasonal morphs of the buckeye butterfly, Precis coenia (Nymphalidae). The ventral surfaces are shown. The Summer morph ("linea") is on the left; the Fall morph ("rosa") is on the right. [Scott F.Gilbert, A Companion to Developmental Biology. Chapter 22, Seasonal Polyphenism in Butterfly Wings]

Damaging nsSNPs

• We estimate that ~20% of non-synonymous cSNPs from databases are damaging

• Average allele frequency of non-synonymous cSNPs predicted to be damaging is twice lower than for benign non-synonymous cSNPs

• We propose to use these predictions for prioritisation of candidates for association studies