1000 Genomes Project

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The 1000 Genomes Project (1KGP), taken place from January 2008 to 2015, was an international research effort to establish the most detailed catalogue of human genetic variation at the time. Scientists planned to sequence the genomes of at least one thousand anonymous healthy participants from a number of different ethnic groups within the following three years, using advancements in newly developed technologies. In 2010, the project finished its pilot phase, which was described in detail in a publication in the journal Nature . [1] In 2012, the sequencing of 1092 genomes was announced in a Nature publication. [2] In 2015, two papers in Nature reported results and the completion of the project and opportunities for future research. [3] [4]

Contents

Many rare variations, restricted to closely related groups, were identified, and eight structural-variation classes were analyzed. [5]

The project united multidisciplinary research teams from institutes around the world, including China, Italy, Japan, Kenya, Nigeria, Peru, the United Kingdom, and the United States contributing to the sequence dataset and to a refined human genome map freely accessible through public databases to the scientific community and the general public alike. [2]

The International Genome Sample Resource was created to host and expand on the data set after the project's end. [6]

Changes in the number and order of genes (A-D) create genetic diversity within and between populations. Genetic Variation.jpg
Changes in the number and order of genes (A-D) create genetic diversity within and between populations.

Background

Since the completion of the Human Genome Project advances in human population genetics and comparative genomics enabled further insight into genetic diversity. [7] The understanding about structural variations (insertions/deletions (indels), copy number variations (CNV), retroelements), single-nucleotide polymorphisms (SNPs), and natural selection were being solidified. [8] [9] [10] [11]

The diversity of Human genetic variation such as that Indels were being uncovered and investigating human genomic variations[ citation needed ]

Natural selection

It also aimed to provide evidence that can be used to explore the impact of Natural selection on population differences. Patterns of DNA polymorphisms can be used to reliably detect signatures of selection and may help to identify genes that might underlie variation in disease resistance or drug metabolism. [12] [13] Such insights could improve understanding of phenotypic variations, genetic disorders and Mendelian inheritance and their effects on survival and/or reproduction of different human populations.

Project description

Goals

The 1000 Genomes Project was designed to bridge the gap of knowledge between rare genetic variants that have a severe effect predominantly on simple traits (e.g. cystic fibrosis, Huntington disease) and common genetic variants have a mild effect and are implicated in complex traits (e.g. cognition, diabetes, heart disease). [14]

The primary goal of this project was to create a complete and detailed catalogue of human genetic variations, which can be used for association studies relating genetic variation to disease. The consortium aimed to discover >95 % of the variants (e.g. SNPs, CNVs, indels) with minor allele frequencies as low as 1% across the genome and 0.1-0.5% in gene regions, as well as to estimate the population frequencies, haplotype backgrounds and linkage disequilibrium patterns of variant alleles. [15]

Secondary goals included the support of better SNP and probe selection for genotyping platforms in future studies and the improvement of the human reference sequence. The completed database was expected be a useful tool for studying regions under selection, variation in multiple populations and understanding the underlying processes of mutation and recombination. [15]

Outline

The human genome consists of approximately 3 billion DNA base pairs and is estimated to carry around 20,000 protein coding genes. In designing the study the consortium needed to address several critical issues regarding the project metrics such as technology challenges, data quality standards and sequence coverage. [15]

Over the course of the next three years,[ clarification needed ] scientists at the Sanger Institute, BGI Shenzhen and the National Human Genome Research Institute’s Large-Scale Sequencing Network planned to sequence a minimum of 1,000 human genomes. Due to the large amount of sequence data that was required, recruiting additional participants was maintained. [14]

Almost 10 billion bases were to be sequenced per day over a period of the two year production phase, equating to more than two human genomes every 24 hours. The intended sequence dataset was to comprise 6 trillion DNA bases, 60-fold more sequence data than what has been published in DNA databases at the time. [14]

To determine the final design of the full project three pilot studies were to be carried out within the first year of the project. The first pilot intends to genotype 180 people of 3 major geographic groups at low coverage (2×). For the second pilot study, the genomes of two nuclear families (both parents and an adult child) are going to be sequenced with deep coverage (20× per genome). The third pilot study involves sequencing the coding regions (exons) of 1,000 genes in 1,000 people with deep coverage (20×). [14] [15]

It was estimated that the project would likely cost more than $500 million if standard DNA sequencing technologies were used. Several newer technologies (e.g. Solexa, 454, SOLiD) were to be applied, lowering the expected costs to between $30 million and $50 million. The major support will be provided by the Wellcome Trust Sanger Institute in Hinxton, England; the Beijing Genomics Institute, Shenzhen (BGI Shenzhen), China; and the NHGRI, part of the National Institutes of Health (NIH). [14]

In keeping with Fort Lauderdale principles Archived 2013-12-28 at the Wayback Machine , all genome sequence data (including variant calls) is freely available as the project progresses and can be downloaded via ftp from the 1000 genomes project webpage.

Human genome samples

Locations of population samples of 1000 Genomes Project. Each circle represents the number of sequences in the final release. 1000 Genomes Project.svg
Locations of population samples of 1000 Genomes Project. Each circle represents the number of sequences in the final release.

Based on the overall goals for the project, the samples will be chosen to provide power in populations where association studies for common diseases are being carried out. Furthermore, the samples do not need to have medical or phenotype information since the proposed catalogue will be a basic resource on human variation. [15]

For the pilot studies human genome samples from the HapMap collection will be sequenced. It will be useful to focus on samples that have additional data available (such as ENCODE sequence, genome-wide genotypes, fosmid-end sequence, structural variation assays, and gene expression) to be able to compare the results with those from other projects. [15]

Complying with extensive ethical procedures, the 1000 Genomes Project will then use samples from volunteer donors. The following populations will be included in the study: Yoruba in Ibadan (YRI), Nigeria; Japanese in Tokyo (JPT); Chinese in Beijing (CHB); Utah residents with ancestry from northern and western Europe (CEU); Luhya in Webuye, Kenya (LWK); Maasai in Kinyawa, Kenya (MKK); Toscani in Italy (TSI); Peruvians in Lima, Peru (PEL); Gujarati Indians in Houston (GIH); Chinese in metropolitan Denver (CHD); people of Mexican ancestry in Los Angeles (MXL); and people of African ancestry in the southwestern United States (ASW). [14]

IDPlacePopulationDetail
ASW Flag of the United States.svg * African Ancestry in Southwestern USA Detail
ACB Flag of Barbados.svg * African Caribbean in Barbados Detail
BEB Flag of Bangladesh.svg Bengali in Bangladesh Detail
GBR Flag of the United Kingdom.svg British from England and Scotland Detail
CDX Flag of the People's Republic of China.svg Chinese Dai in Xishuangbanna, China Detail
CLM Flag of Colombia.svg Colombian in Medellín, Colombia Detail
ESN Flag of Nigeria.svg Esan in Nigeria Detail
FIN Flag of Finland.svg Finnish in Finland Detail
GWD Flag of The Gambia.svg Gambian in Western DivisionMandinka Detail
GIH Flag of the United States.svg * Gujarati Indians in Houston, Texas, United States Detail
CHB Flag of the People's Republic of China.svg Han Chinese in Beijing, China Detail
CHS Flag of the People's Republic of China.svg Han Chinese South, China Detail
IBS Flag of Spain.svg Iberian populations in Spain Detail
ITU Flag of the United Kingdom.svg * Indian Telugu in the U.K. Detail
JPT Flag of Japan.svg Japanese in Tokyo, Japan Detail
KHV Flag of Vietnam.svg Kinh in Ho Chi Minh City, Vietnam Detail
LWK Flag of Kenya.svg Luhya in Webuye, Kenya Detail
MSL Flag of Sierra Leone.svg Mende in Sierra Leone Detail
MXL Flag of the United States.svg * Mexican Ancestry in Los Angeles, California, United States Detail
PEL Flag of Peru.svg Peruvian in Lima, Peru Detail
PUR Flag of Puerto Rico.svg Puerto Rican in Puerto Rico Detail
PJL Flag of Pakistan.svg Punjabi in Lahore, Pakistan Detail
STU Flag of the United Kingdom.svg * Sri Lankan Tamil in the U.K. Detail
TSI Flag of Italy.svg Toscani in Italia Detail
YRI Flag of Nigeria.svg Yoruba in Ibadan, Nigeria Detail
CEU Flag of the United States.svg * Utah residents with Northern and Western European ancestry from the CEPH collection Detail

* Population that was collected in diaspora

Community meeting

Data generated by the 1000 Genomes Project is widely used by the genetics community, making the first 1000 Genomes Project one of the most cited papers in biology. [17] To support this user community, the project held a community analysis meeting in July 2012 that included talks highlighting key project discoveries, their impact on population genetics and human disease studies, and summaries of other large-scale sequencing studies. [18]

Project findings

Pilot phase

The pilot phase consisted of three projects:

It was found that on average, each person carries around 250–300 loss-of-function variants in annotated genes and 50-100 variants previously implicated in inherited disorders. Based on the two trios, it is estimated that the rate of de novo germline mutation is approximately 10−8 per base per generation. [1]

See also

Related Research Articles

<span class="mw-page-title-main">Human genome</span> Complete set of nucleic acid sequences for humans

The human genome is a complete set of nucleic acid sequences for humans, encoded as DNA within the 23 chromosome pairs in cell nuclei and in a small DNA molecule found within individual mitochondria. These are usually treated separately as the nuclear genome and the mitochondrial genome. Human genomes include both protein-coding DNA sequences and various types of DNA that does not encode proteins. The latter is a diverse category that includes DNA coding for non-translated RNA, such as that for ribosomal RNA, transfer RNA, ribozymes, small nuclear RNAs, and several types of regulatory RNAs. It also includes promoters and their associated gene-regulatory elements, DNA playing structural and replicatory roles, such as scaffolding regions, telomeres, centromeres, and origins of replication, plus large numbers of transposable elements, inserted viral DNA, non-functional pseudogenes and simple, highly repetitive sequences. Introns make up a large percentage of non-coding DNA. Some of this non-coding DNA is non-functional junk DNA, such as pseudogenes, but there is no firm consensus on the total amount of junk DNA.

<span class="mw-page-title-main">Genomics</span> Discipline in genetics

Genomics is an interdisciplinary field of biology focusing on the structure, function, evolution, mapping, and editing of genomes. A genome is an organism's complete set of DNA, including all of its genes as well as its hierarchical, three-dimensional structural configuration. In contrast to genetics, which refers to the study of individual genes and their roles in inheritance, genomics aims at the collective characterization and quantification of all of an organism's genes, their interrelations and influence on the organism. Genes may direct the production of proteins with the assistance of enzymes and messenger molecules. In turn, proteins make up body structures such as organs and tissues as well as control chemical reactions and carry signals between cells. Genomics also involves the sequencing and analysis of genomes through uses of high throughput DNA sequencing and bioinformatics to assemble and analyze the function and structure of entire genomes. Advances in genomics have triggered a revolution in discovery-based research and systems biology to facilitate understanding of even the most complex biological systems such as the brain.

Molecular evolution is the process of change in the sequence composition of cellular molecules such as DNA, RNA, and proteins across generations. The field of molecular evolution uses principles of evolutionary biology and population genetics to explain patterns in these changes. Major topics in molecular evolution concern the rates and impacts of single nucleotide changes, neutral evolution vs. natural selection, origins of new genes, the genetic nature of complex traits, the genetic basis of speciation, the evolution of development, and ways that evolutionary forces influence genomic and phenotypic changes.

<span class="mw-page-title-main">Single-nucleotide polymorphism</span> Single nucleotide in genomic DNA at which different sequence alternatives exist

In genetics and bioinformatics, a single-nucleotide polymorphism is a germline substitution of a single nucleotide at a specific position in the genome that is present in a sufficiently large fraction of considered population.

The International HapMap Project was an organization that aimed to develop a haplotype map (HapMap) of the human genome, to describe the common patterns of human genetic variation. HapMap is used to find genetic variants affecting health, disease and responses to drugs and environmental factors. The information produced by the project is made freely available for research.

Indel (insertion-deletion) is a molecular biology term for an insertion or deletion of bases in the genome of an organism. Indels ≥ 50 bases in length are classified as structural variants.

<span class="mw-page-title-main">Human genetic variation</span> Genetic diversity in human populations

Human genetic variation is the genetic differences in and among populations. There may be multiple variants of any given gene in the human population (alleles), a situation called polymorphism.

Human evolutionary genetics studies how one human genome differs from another human genome, the evolutionary past that gave rise to the human genome, and its current effects. Differences between genomes have anthropological, medical, historical and forensic implications and applications. Genetic data can provide important insights into human evolution.

<span class="mw-page-title-main">Genome-wide association study</span> Study of genetic variants in different individuals

In genomics, a genome-wide association study, is an observational study of a genome-wide set of genetic variants in different individuals to see if any variant is associated with a trait. GWA studies typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits like major human diseases, but can equally be applied to any other genetic variants and any other organisms.

Minor allele frequency (MAF) is the frequency at which the second most common allele occurs in a given population. They play a surprising role in heritability since MAF variants which occur only once, known as "singletons", drive an enormous amount of selection.

Population genomics is the large-scale comparison of DNA sequences of populations. Population genomics is a neologism that is associated with population genetics. Population genomics studies genome-wide effects to improve our understanding of microevolution so that we may learn the phylogenetic history and demography of a population.

<span class="mw-page-title-main">Whole genome sequencing</span> Determining nearly the entirety of the DNA sequence of an organisms genome at a single time

Whole genome sequencing (WGS), also known as full genome sequencing, complete genome sequencing, or entire genome sequencing, is the process of determining the entirety, or nearly the entirety, of the DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.

<span class="mw-page-title-main">Exome sequencing</span> Sequencing of all the exons of a genome

Exome sequencing, also known as whole exome sequencing (WES), is a genomic technique for sequencing all of the protein-coding regions of genes in a genome. It consists of two steps: the first step is to select only the subset of DNA that encodes proteins. These regions are known as exons—humans have about 180,000 exons, constituting about 1% of the human genome, or approximately 30 million base pairs. The second step is to sequence the exonic DNA using any high-throughput DNA sequencing technology.

<span class="mw-page-title-main">Reference genome</span> Digital nucleic acid sequence database

A reference genome is a digital nucleic acid sequence database, assembled by scientists as a representative example of the set of genes in one idealized individual organism of a species. As they are assembled from the sequencing of DNA from a number of individual donors, reference genomes do not accurately represent the set of genes of any single individual organism. Instead, a reference provides a haploid mosaic of different DNA sequences from each donor. For example, one of the most recent human reference genomes, assembly GRCh38/hg38, is derived from >60 genomic clone libraries. There are reference genomes for multiple species of viruses, bacteria, fungus, plants, and animals. Reference genomes are typically used as a guide on which new genomes are built, enabling them to be assembled much more quickly and cheaply than the initial Human Genome Project. Reference genomes can be accessed online at several locations, using dedicated browsers such as Ensembl or UCSC Genome Browser.

Genomic structural variation is the variation in structure of an organism's chromosome. It consists of many kinds of variation in the genome of one species, and usually includes microscopic and submicroscopic types, such as deletions, duplications, copy-number variants, insertions, inversions and translocations. Originally, a structure variation affects a sequence length about 1kb to 3Mb, which is larger than SNPs and smaller than chromosome abnormality. However, the operational range of structural variants has widened to include events > 50bp. The definition of structural variation does not imply anything about frequency or phenotypical effects. Many structural variants are associated with genetic diseases, however many are not. Recent research about SVs indicates that SVs are more difficult to detect than SNPs. Approximately 13% of the human genome is defined as structurally variant in the normal population, and there are at least 240 genes that exist as homozygous deletion polymorphisms in human populations, suggesting these genes are dispensable in humans. Rapidly accumulating evidence indicates that structural variations can comprise millions of nucleotides of heterogeneity within every genome, and are likely to make an important contribution to human diversity and disease susceptibility.

<span class="mw-page-title-main">Jumping library</span>

Jumping libraries or junction-fragment libraries are collections of genomic DNA fragments generated by chromosome jumping. These libraries allow the analysis of large areas of the genome and overcome distance limitations in common cloning techniques. A jumping library clone is composed of two stretches of DNA that are usually located many kilobases away from each other. The stretch of DNA located between these two "ends" is deleted by a series of biochemical manipulations carried out at the start of this cloning technique.

Philip Awadalla is a professor of medical and population genetics at the Ontario Institute for Cancer Research, and the Department of Molecular Genetics, Faculty of Medicine, University of Toronto. He is the National Scientific Director of the Canadian Partnership for Tomorrow's Health (CanPath), formerly the Canadian Partnership for Tomorrow Project (CPTP), and executive director of the Ontario Health Study. He is also the Executive Scientific Director of the Genome Canada Genome Technology Platform, the Canadian Data Integration Centre. Professor Awadalla was the Executive Scientific Director of the CARTaGENE biobank, a regional cohort member of the CPTP, from 2009 to 2015, and is currently a scientific advisor for this and other scientific and industry platforms. At the OICR, he is Director of Computational Biology.

Imputation in genetics refers to the statistical inference of unobserved genotypes. It is achieved by using known haplotypes in a population, for instance from the HapMap or the 1000 Genomes Project in humans, thereby allowing to test for association between a trait of interest and experimentally untyped genetic variants, but whose genotypes have been statistically inferred ("imputed"). Genotype imputation is usually performed on SNPs, the most common kind of genetic variation.

<span class="mw-page-title-main">Structural variation in the human genome</span> Genomic alterations, varying between individuals

Structural variation in the human genome is operationally defined as genomic alterations, varying between individuals, that involve DNA segments larger than 1 kilo base (kb), and could be either microscopic or submicroscopic. This definition distinguishes them from smaller variants that are less than 1 kb in size such as short deletions, insertions, and single nucleotide variants.

ANNOVAR is a bioinformatics software tool for the interpretation and prioritization of single nucleotide variants (SNVs), insertions, deletions, and copy number variants (CNVs) of a given genome.

References

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