A panorama of mammalian gene expression evolution

Widely distributed hot and cold spots in meiotic recombination as shown by the sequencing of rice F2 plants

Numerous studies have argued that environmental variations may contribute to evolution through the generation of novel heritable variations via meiotic recombination, which plays a crucial role in crop domestication and improvement. Rice is one of the most important staple crops, but no direct estimate of recombination events has yet been made at a fine scale. Here, we address this limitation by sequencing 41 rice individuals with high sequencing coverage and c. 900 000 accurate markers. An average of 33.9 crossover (c. 4.53 cM Mb(-1) ) and 2.47 non-crossover events were detected per F2 plant, which is similar to the values in Arabidopsis. Although not all samples in the stress treatment group showed an increased number of crossover events, environmental stress increased the recombination rate in c. 28.5% of samples. Interestingly, the crossovers showed a highly uneven distribution among and along chromosomes, with c. 13.9% of the entire genome devoid of crossovers, including 11 of the 12 centromere regions, and c. 0.72% of the genome containing large numbers of crossovers (> 50 cM Mb(-1) ). The gene ontology (GO) categories showed that genes clustered within the recombination hot spot regions primarily tended to be involved in responses to environmental stimuli, suggesting that recombination plays an important role for adaptive evolution in rapidly changing environments.

The ortholog conjecture is untestable by the current gene ontology but is supported by RNA sequencing data

The ortholog conjecture posits that orthologous genes are functionally more similar than paralogous genes. This conjecture is a cornerstone of phylogenomics and is used daily by both computational and experimental biologists in predicting, interpreting, and understanding gene functions. A recent study, however, challenged the ortholog conjecture on the basis of experimentally derived Gene Ontology (GO) annotations and microarray gene expression data in human and mouse. It instead proposed that the functional similarity of homologous genes is primarily determined by the cellular context in which the genes act, explaining why a greater functional similarity of (within-species) paralogs than (between-species) orthologs was observed. Here we show that GO-based functional similarity between human and mouse orthologs, relative to that between paralogs, has been increasing in the last five years. Further, compared with paralogs, orthologs are less likely to be included in the same study, causing an underestimation in their functional similarity. A close examination of functional studies of homologs with identical protein sequences reveals experimental biases, annotation errors, and homology-based functional inferences that are labeled in GO as experimental. These problems and the temporary nature of the GO-based finding make the current GO inappropriate for testing the ortholog conjecture. RNA sequencing (RNA-Seq) is known to be superior to microarray for comparing the expressions of different genes or in different species. Our analysis of a large RNA-Seq dataset of multiple tissues from eight mammals and the chicken shows that the expression similarity between orthologs is significantly higher than that between within-species paralogs, supporting the ortholog conjecture and refuting the cellular context hypothesis for gene expression. We conclude that the ortholog conjecture remains largely valid to the extent that it has been tested, but further scrutiny using more and better functional data is needed.