Most Mutations Come from Dad

6 09 2012

New insights into age, height and sex reshape views of human evolution

 

By R. ALAN LEO. Humans inherit more than three times as many mutations from their fathers as from their mothers, and mutation rates increase with the father’s age but not the mother’s, researchers have found in the largest study of human genetic mutations to date.

The study, based on the DNA of around 85,000 Icelanders, also calculates the rate of human mutation at high resolution, providing estimates of when human ancestors diverged from nonhuman primates. It is one of two papers published this week by the journal Nature Genetics as well as one published at Nature that shed dramatic new light on human evolution.

James Sun/Harvard Medical School

James Sun/Harvard Medical School

“Most mutations come from dad,” said David Reich, professor of genetics at Harvard Medical School and a co-leader of the study. In addition to finding 3.3 paternal germline mutations for each maternal mutation, the study also found that the mutation rate in fathers doubles from age 20 to 58 but that there is no association with age in mothers — a finding that may shed light on conditions, such as autism, that correlate with the father’s age.

The study’s first author is James Sun, a graduate student in Reich’s lab who worked with researchers from deCODE Genetics, a biopharma company based in Reykjavik, Iceland, to analyze about 2,500 short sequences of DNA taken from 85,289 Icelanders in 24,832 father-mother-child trios. The sequences, called microsatellites, vary in the number of times that they repeat, and are known to mutate at a higher rate than average places in the genome.

Reich’s team identified 2,058 mutational changes, yielding a rate of mutation that suggests human and chimpanzee ancestral populations diverged between 3.7 million and 6.6 million years ago.

A second team, also based at deCODE Genetics (but not involving HMS researchers), published a paper this week in Nature on a large-scale direct estimate of the rate of single nucleotide substitutions in human genomes (a different type of mutation process), and came to largely consistent findings.

The finding complicates theories drawn from the fossil evidence. The upper bound, 6.6 million years, is less than the published date of Sahelanthropus tchadensis, a fossil that has been interpreted to be a human ancestor since the separation of chimpanzees, but is dated to around 7 million years old. The new study suggests that this fossil may be incorrectly interpreted.

Great Heights

A second study led by HMS researchers, also published in Nature Genetics this week, adds to the picture of human evolution, describing a newly observable form of recent genetic adaptation.

The team led by Joel Hirschhorn, Concordia Professor of Pediatrics and professor of genetics at Boston Children’s Hospital and HMS, first asked why closely-related populations can have noticeably different average heights. David Reich also contributed to this study.

They examined genome-wide association data and found that average differences in height across Europe are partly due to genetic factors. They then showed that these genetic differences are the result of an evolutionary process that acts on variation in many genes at once. This type of evolution had been proposed to exist but had not previously been detected in humans.

Although recent human evolution is difficult to observe directly, some of its impact can be inferred by studying the human genome. In recent years, genetic studies have uncovered many examples where recent evolution has left a distinctive signature on the human genome. The clearest “footprints” of evolution have been seen in regions of DNA surrounding mutations that occurred fairly recently (typically in the last several thousand years) and confer an advantageous trait, such as resistance to malaria. Hirschhorn’s team observed, for the first time in humans, a different signature of recent evolution: widespread small but consistent changes at many different places in the genome, all affecting the same trait, adult height.

“This paper offers the first proof and clear example of a new kind of human evolution for a specific trait,” said Hirschhorn, who is also a senior associate member of the Broad Institute. “We provide a demonstration of how humans have been able to adapt rapidly without needing to wait for new mutations to happen, by drawing instead on the existing genetic diversity within the human population.”

Average heights can differ between populations, even populations that are genetically very similar, which suggests that human height might have been evolving differently across these populations. Hirschhorn’s team studied variants in the genome that are known to have small but consistent effects on height: people inheriting the “tall” version of these variants are known to be slightly taller on average than people inheriting the “short” versions of the same variants.

The researchers discovered that, in northern Europe, the “tall” versions of these variants are consistently a little more common than they are in southern Europe. The combined effects of the “tall” versions being more common can partly explain why northern Europeans are on average taller than southern Europeans. The researchers then showed that these slight differences have arisen as a result of evolution acting at many variants, and acting differently in northern than in southern Europe.

“This paper explains — at least in part — why some European populations, such as people from Sweden, are taller on average than others, such as people from Italy,” Hirschhorn said.

The researchers were only able to detect this signature of evolution by using the results of recent genome-wide association studies by the GIANT consortium, which identified hundreds of different genetic variants that influence height.

Funding

The Reich/deCODE study was supported by a Bioinformatics and Integrative Genomics PhD training grant (JXS), a Burroughs Wellcome Travel Grant (JXS), a Burroughs Wellcome Career Development Award in the Biomedical Sciences (DR), a HUSEC seed grant from Harvard University (DR), a SPARC award from the Broad Institute of Harvard and MIT (DR), National Science Foundation HOMINID grant 1032255 (DR), and National Institute of Health grant R01HG006399 (DR).

The Hirschhorn study was supported by the National Heart, Lung and Blood Institute’s FHS (contract no. N01-HC-25195) and its contract with Affymetrix, Inc., for genotyping services (contract no. N02-HL-6-4278). A portion of this research used the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. This work was also supported by a graduate research fellowship from the National Science Foundation (to C.W.K.C.), the March of Dimes (6-FY09-507 to J.N.H.) and the National Institute of Diabetes and Digestive and Kidney Diseases (1R01DK075787 to J.N.H.).

hms.harvard.edu [en línea] Boston (USA): hms.harvard.edu, 06 de septiembre de 2012 [ref. 23 de agosto de 2012] Disponible en Internet: http://hms.harvard.edu/content/most-mutations-come-dad



New Web Tool Helps Researchers Explore How the Genome Changes in Cancer

5 07 2012

Scientists at Memorial Sloan-Kettering have launched a new web-based tool to make information from large-scale genome-sequencing projects easier for researchers to navigate and explore.

The publicly accessible tool — called the cBio Cancer Genomics Portal — empowers cancer biologists and clinicians to translate complex data gathered about gene alterations into new cancer insights and clinical applications, the inventors write in a report published in the May issue of the journal Cancer Discovery.

 

Gynecologic oncologist Douglas Levine (left) and postdoctoral research fellow Petar Jelinic are using the new web tool to explore genetic changes that occur in ovarian cancer.

Gynecologic oncologist Douglas Levine (left) and postdoctoral research fellow Petar Jelinic are using the new web tool to explore genetic changes that occur in ovarian cancer.

“Now scientists can quickly extract the particular slice of information they need from genome databases without having to deal with the bulk of data that isn’t relevant to their research,” explains computational biologist Nikolaus Schultz, who led the development of the cBio Cancer Genomics Portal together with co-author Ethan Cerami. In addition, the resource facilitates the analysis of different types of data and presents the results in graphical summaries.

“Essentially, you can turn spreadsheets with millions of numbers into diagrams that reveal what happens to genes in cancer — without having to be an expert in genome analysis,” Dr. Schultz adds.

Information Overload

Investigators in the field have collaborated nationally and globally in recent years to catalog the myriad genetic changes that occur in tumors. For example, The Cancer Genome Atlas (TCGA) — a genome-sequencing project launched by the National Cancer Institute and the National Human Genome Research Institute in 2006 — is amassing genomic and clinical information from patients with more than 20 types of cancer.

A goal of these types of collaborations is to fast-track the understanding of the basic mechanisms of cancer — for example, by determining how certain alterations in the genome may initiate the formation of tumors, change the behavior of tumors after they have formed, or affect their response to therapy. Such knowledge could ultimately result in better methods to diagnose and control cancers, or prevent the disease from occurring in the first place.

But according to Chris Sander, Chair of the Sloan-Kettering Institute’s Computational Biology Program and one of the report’s authors, the speed of progress is now limited by the complex task of translating massive molecular data into insights that ultimately could benefit patients.

“The amount of detailed information from thousands of tumor samples stored in public genome databases is overwhelming and continues to grow rapidly as the result of national and international efforts,” Dr. Sander explains. When completed, The Cancer Genome Atlas will have mapped the genomes of more than 20,000 tumors, with diverse types of genetic changes documented for each sample.

“The community of cancer researchers is now tackling the challenge of translating the atlas into useful insights about the genes and physiological processes that are rewired in cancer, and the way these changes might affect disease outcome,” Dr. Sander adds.

Bridging a Knowledge Gap

The relationship between genes and cancer is inherently complicated. For example, the function of a gene can be affected by alterations of the DNA sequence, as well as by epigenetic changes, which leave the genetic code unchanged while modifying the activity of genes. Cancer is often the result of a complex mixture of genetic and epigenetic changes occurring in many genes over time.

To date, the new resource provides researchers easy access to five types of changes affecting thousands of cancer-associated genes, which have been mapped out in 17 diseases. The data has been generated by TCGA and by two independent Memorial Sloan-Kettering projects, which provided the first comprehensive analyses of gene changes in prostate cancer and sarcoma. Information generated in additional projects — including those coordinated by the International Cancer Genome Consortium — will soon be included.

“Our tool was designed to bridge a knowledge gap between computational and systems biologists on the one hand, and cancer researchers and disease experts on the other hand,” says Dr. Sander. “The feedback from the scientific community has been very enthusiastic.”

“It’s incredibly rewarding to know that more and more people are using our resource,” adds Dr. Schultz, “and to hear that it’s helping them capture the essence of what happens with the genome in cancer.”

This research was supported by the National Cancer Institute of the National Institutes of Health under award numbers NCI-U24CA143840 and NCI-R21CA135870.

 

Mskcc.org [en línea] NY (USA): mskcc.org, 05 de julio de 2012 [ref. 21 de junio de 2012] Disponible en Internet: http://www.mskcc.org/news/announcement/new-web-tool-helps-researchers-explore-how-genome-changes