Complete Human Recombination Maps

Genetics Life Sciences Medicine
recombination maps non-cross-over recombination sex-specific mutations meiosis

Complete Human Recombination Maps

Academic Background

In genetic research, recombination is one of the key mechanisms by which organisms generate genetic diversity. Recombination not only affects the transmission and combination of genes but also plays a crucial role in natural selection and population history inference. However, existing recombination maps are primarily based on cross-over (CO) events, while the more common non-cross-over (NCO) events have been largely overlooked. The difficulty in detecting NCOs has led to their contribution being underestimated in recombination studies. To fully understand the mechanisms of recombination and their impact on genetic diversity, researchers need to construct complete recombination maps that include both COs and NCOs.

This study aims to estimate the number of NCOs transmitted from parents to offspring using whole-genome sequencing data and to construct sex-specific recombination maps that include both COs and NCOs. This research not only fills the gaps in existing recombination maps but also provides new insights into the differences in recombination between sexes, the impact of maternal age on recombination, and the contribution of recombination to de novo mutations (DNMs).

Source of the Paper

This paper was co-authored by researchers from deCODE Genetics/Amgen Inc., including Gunnar Pálsson, Marteinn T. Hardarson, Hákon Jónsson, and others. The research team also includes scholars from Reykjavik University, the University of Iceland, and several other institutions. The paper was published online in Nature on November 25, 2024, under the title “Complete human recombination maps.”

Research Process

1. Data Collection and Processing

The research team used whole-genome sequencing data from 2,132 Icelandic families, comprising 5,420 trios (parents and at least two children). These data were derived from deCODE Genetics’ disease association studies, covering 173,025 individuals genotyped using SNP chips, of which 63,118 individuals underwent whole-genome sequencing. By analyzing these data, the researchers detected gene conversion events transmitted from parents to offspring and constructed recombination maps that include both COs and NCOs.

2. Detection of Gene Conversions

Gene conversions were detected by phasing the genotypes of parents and children. The researchers first performed phasing analysis on the genotypes of parents and children to determine the haplotype origins of each child. When one parent was heterozygous at a specific locus and the other was homozygous, the locus was considered an informative marker. By analyzing these informative markers, the researchers were able to detect gene conversion events.

3. Length Distribution and Estimation of NCOs

The researchers used a custom algorithm called NCOURD to model the length distribution of NCOs. This algorithm is based on a mixture of negative binomial distributions and can estimate the number of unobserved NCOs. Using this method, the researchers estimated the average number of NCOs per offspring and further estimated the number of double-strand breaks (DSBs) per germ cell.

4. Construction of Recombination Maps

The researchers constructed sex-specific NCO recombination maps and combined them with existing CO recombination maps to generate complete recombination maps that include both COs and NCOs. These maps were constructed using overlapping 3 Mb windows, achieving a resolution comparable to early CO maps. By analyzing these maps, the researchers explored how DSBs are resolved in different genomic regions.

5. Analysis of De Novo Mutations

The researchers also analyzed DNMs near NCOs and found a significant correlation between NCOs and DNMs. By comparing the mutation spectra of DNMs near NCOs and COs, the researchers revealed the contribution of NCOs to DNMs and estimated the overall contribution of recombination to DNMs.

Key Findings

1. Number and Length Distribution of NCOs

The study found that mothers transmit fewer NCOs, but these NCOs are longer. The average number of NCOs per offspring was 105.0 for fathers and 81.6 for mothers. The length distribution of NCOs showed that the average length of short NCOs (<1 kb) was 123 bp for fathers and 102 bp for mothers, while the average length of long NCOs (>1 kb) was 7.2 kb for fathers and 9.1 kb for mothers.

2. Sex Differences in Recombination Maps

The study revealed significant differences between paternal and maternal NCO recombination maps. Paternal NCO recombination rates were significantly elevated near telomeres, while maternal NCO recombination rates showed a milder elevation near telomeres. Additionally, there were sex differences in the resolution of NCOs near centromeres, with paternal NCOs showing more pronounced resolution near centromeres.

3. Contribution of NCOs to DNMs

The study found a significant correlation between NCOs and DNMs. Within 1 kb of the NCO center, the DNM rate increased by 142-fold for fathers and 125-fold for mothers. The researchers estimated that recombination (primarily NCOs) contributes 1.8% and 11.3% to paternal and maternal DNMs, respectively.

4. Impact of Maternal Age on NCOs

The study found that the number of maternal NCOs increases with age. The number of maternal NCOs increased by 20.3 per decade. This increase primarily occurred outside DMC1 hotspot regions, suggesting that the resolution of maternal NCOs becomes less tightly regulated with age.

Conclusions and Significance

This study is the first to construct complete human recombination maps that include both COs and NCOs, filling a significant gap in existing recombination maps. The research highlights the important role of NCOs in recombination, particularly in sex differences and the impact of maternal age on recombination. Additionally, the study reveals the contribution of NCOs to DNMs, providing new insights into the relationship between recombination and mutation.

Scientific Value

  1. Filling the Gap in Recombination Maps: This study is the first to incorporate NCOs into recombination maps, providing an essential tool for understanding the complete mechanisms of recombination.
  2. Revealing Sex Differences: The study reveals significant differences in the number and length distribution of NCOs between fathers and mothers, offering new perspectives on sex differences in recombination.
  3. Impact of Maternal Age: The study demonstrates the impact of maternal age on the number of NCOs, providing new evidence for understanding the influence of maternal age on genetic diversity.
  4. Relationship Between Recombination and Mutation: The study reveals the contribution of NCOs to DNMs, offering new insights into the relationship between recombination and mutation.

Application Value

  1. Genetic Disease Research: This study provides new tools for understanding the mechanisms of genetic diseases, particularly those related to recombination.
  2. Reproductive Health: The study highlights the impact of maternal age on recombination, offering new approaches to improving reproductive health in older mothers.
  3. Evolutionary Biology: The study provides new perspectives on the mechanisms of human genetic diversity, helping to uncover the mysteries of human evolution.

Research Highlights

  1. First Complete Recombination Maps Including NCOs: This study fills the gap in existing recombination maps, providing an essential tool for understanding the complete mechanisms of recombination.
  2. Revealing Sex Differences and the Impact of Maternal Age: The study reveals significant differences in the number and length distribution of NCOs between fathers and mothers, as well as the impact of maternal age on the number of NCOs.
  3. Contribution of NCOs to DNMs: The study reveals the contribution of NCOs to DNMs, offering new insights into the relationship between recombination and mutation.

Additional Valuable Information

This study also provides detailed NCO recombination maps and DNM analysis data, which are available through the Zenodo platform. Additionally, the research team developed the NCOURD algorithm for modeling the length distribution of NCOs, which is also available on GitHub.