Similarity in Recombination Rate Estimates Highly Correlates with Genetic Differentiation in Humans

Recombination varies greatly among species, as illustrated by the poor conservation of the recombination landscape between humans and chimpanzees. Thus, shorter evolutionary time frames are needed to understand the evolution of recombination. Here, we analyze its recent evolution in humans. We calculated the recombination rates between adjacent pairs of 636,933 common single-nucleotide polymorphism loci in 28 worldwide human populations and analyzed them in relation to genetic distances between populations. We found a strong and highly significant correlation between similarity in the recombination rates corrected for effective population size and genetic differentiation between populations. This correlation is observed at the genome-wide level, but also for each chromosome and when genetic distances and recombination similarities are calculated independently from different parts of the genome. Moreover, and more relevant, this relationship is robustly maintained when considering presence/absence of recombination hotspots. Simulations show that this correlation cannot be explained by biases in the inference of recombination rates caused by haplotype sharing among similar populations. This result indicates a rapid pace of evolution of recombination, within the time span of differentiation of modern humans

Application of Multi-SNP Approaches Bayesian LASSO and AUC-RF to Detect Main Effects of Inflammatory-Gene Variants Associated with Bladder Cancer Risk

The relationship between inflammation and cancer is well established in several tumor types, including bladder cancer. We performed an association study between 886 inflammatory-gene variants and bladder cancer risk in 1,047 cases and 988 controls from the Spanish Bladder Cancer (SBC)/EPICURO Study. A preliminary exploration with the widely used univariate logistic regression approach did not identify any significant SNP after correcting for multiple testing. We further applied two more comprehensive methods to capture the complexity of bladder cancer genetic susceptibility: Bayesian Threshold LASSO (BTL), a regularized regression method, and AUC-Random Forest, a machine-learning algorithm. Both approaches explore the joint effect of markers. BTL analysis identified a signature of 37 SNPs in 34 genes showing an association with bladder cancer. AUC-RF detected an optimal predictive subset of 56 SNPs. 13 SNPs were identified by both methods in the total population. Using resources from the Texas Bladder Cancer study we were able to replicate 30% of the SNPs assessed. The associations between inflammatory SNPs and bladder cancer were reexamined among non-smokers to eliminate the effect of tobacco, one of the strongest and most prevalent environmental risk factor for this tumor. A 9 SNP-signature was detected by BTL. Here we report, for the first time, a set of SNP in inflammatory genes jointly associated with bladder cancer risk. These results highlight the importance of the complex structure of genetic susceptibility associated with cancer risk.The work was partially supported by the Fondo de Investigacion Sanitaria, Instituto de Salud Carlos III (G03/174, 00/0745, PI051436, PI061614, PI09-02102, G03/174 and Sara Borrell fellowship to ELM) and Ministry of Science and Innovation (MTM2008-06747-C02-02 and FPU fellowship award to VU), Spain; AGAUR-Generalitat de Catalunya (Grant 2009SGR-581); Fundaciola Maratode TV3; Red Tematica de Investigacion Cooperativa en Cancer (RTICC); Asociacion Espanola Contra el Cancer (AECC); EU-FP7-201663; and RO1-CA089715 and CA34627; the Spanish National Institute for Bioinformatics (www.inab.org); and by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, USA. MD Anderson support for this project included U01 CA 127615 (XW); R01 CA 74880 (XW); P50 CA 91846 (XW, CPD); Betty B. Marcus Chair fund in Cancer Prevention (XW); UT Research Trust fund (XW) and R01 CA 131335 (JG)

The genome sequencing of an albino Western lowland gorilla reveals inbreeding in the wild

Altres ajuts: ERC grant: ERC-2010-StG_20091118. The Andalusian Government for grants CSD2007-00008 and CVI-3488, supported by FEDER to JLG-S The Barcelona Zoo (Ajuntament de Barcelona) for an award to JP-M. EEE is an investigator with the Howard Hughes Medical InstituteBackground: the only known albino gorilla, named Snowflake, was a male wild born individual from Equatorial Guinea who lived at the Barcelona Zoo for almost 40 years. He was diagnosed with non-syndromic oculocutaneous albinism, i.e. white hair, light eyes, pink skin, photophobia and reduced visual acuity. Despite previous efforts to explain the genetic cause, this is still unknown. Here, we study the genetic cause of his albinism and making use of whole genome sequencing data we find a higher inbreeding coefficient compared to other gorillas.- Results: we successfully identified the causal genetic variant for Snowflake's albinism, a non-synonymous single nucleotide variant located in a transmembrane region of SLC45A2. This transporter is known to be involved in oculocutaneous albinism type 4 (OCA4) in humans. We provide experimental evidence that shows that this amino acid replacement alters the membrane spanning capability of this transmembrane region. Finally, we provide a comprehensive study of genome-wide patterns of autozygogosity revealing that Snowflake's parents were related, being this the first report of inbreeding in a wild born Western lowland gorilla.- Conclusions: in this study we demonstrate how the use of whole genome sequencing can be extended to link genotype and phenotype in non-model organisms and it can be a powerful tool in conservation genetics (e.g., inbreeding and genetic diversity) with the expected decrease in sequencing cos