Mutations that have occurred in human genomes provide insight into various aspects of evolutionary history such as speciation events and degrees of natural selection. Comparing genome sequences between human and great apes or among humans is a feasible approach for inferring human evolutionary history. Recent advances in high-throughput or so-called ‘next-generation’ DNA sequencing technologies have enabled the sequencing of thousands of individual human genomes, as well as a variety of reference genomes of hominids, many of which are publicly available. These sequence data can help to unveil the detailed demographic history of the lineage leading to humans as well as the explosion of modern human population size in the last several thousand years. In addition, high-throughput sequencing illustrates the tempo and mode of de novo mutations, which are producing human genetic variation at this moment. Pedigree-based human genome sequencing has shown that mutation rates vary significantly across the human genome. These studies have also provided an improved timescale of human evolution, because the mutation rate estimated from pedigree analysis is half that estimated from traditional analyses based on molecular phylogeny. Because of the dramatic reduction in sequencing cost, sequencing on-demand samples designed for specific studies is now also becoming popular. To produce data of sufficient quality to meet the requirements of the study, it is necessary to set an explicit sequencing plan that includes the choice of sample collection methods, sequencing platforms, and number of sequence reads.
Genetic diversity is a key parameter in population genetics and is important for understanding the process of evolution and for the development of appropriate conservation strategies. Recent advances in sequencing technology have enabled the measurement of genetic diversity of various organisms at the nucleotide level and on a genome-wide scale, yielding more precise estimates than were previously achievable. In this review, I have compiled and summarized the estimates of genetic diversity in humans and non-human primates based on recent genome-wide studies. Although studies on population genetics demonstrated fluctuations in population sizes over time, general patterns have emerged. As shown previously, genetic diversity in humans is one of the lowest among primates; however, certain other primate species exhibit genetic diversity that is comparable to or even lower than that in humans. There exists greater than 10-fold variation in genetic diversity among primate species, and I found weak correlation with species fecundity but not with body or propagule size. I further discuss the potential evolutionary consequences of population size decline on the evolution of primate species. The level of genetic diversity negatively correlates with the ratio of non-synonymous to synonymous polymorphisms in a population, suggesting that proportionally greater numbers of slightly deleterious mutations segregate in small rather than large populations. Although population size decline is likely to promote the fixation of slightly deleterious mutations, there are molecular mechanisms, such as compensatory mutations at various molecular levels, which may prevent fitness decline at the population level. The effects of slightly deleterious mutations from theoretical and empirical studies and their relevance to conservation biology are also discussed in this review.
The Japanese Archipelago stretches approximately 3,000 kilometers from Hokkaido in the north to the Ryukyu Islands in the south, and has seen human activity since at least 30 thousand years ago (KYA). The Jomon period from 16 to 3 KYA is associated with cord-marked pottery and the people at that time, who were hunter-gatherers, occupied a range of locations across the Japanese Archipelago. The Yayoi period from 3 to 1.7 KYA saw the introduction of migrants from the Asian Continent who brought rice agriculture to the archipelago. The dual-structure model, which is based on craniofacial measurements, proposes that admixture between the Jomon and Yayoi people resulted in current-day Japanese. Subsequent genetic studies using uniparental and autosomal markers in current-day and ancient human samples are widely in support of the dual-structure model. These genetic data have also unveiled the uniqueness of the indigenous Ainu and Ryukyuan people while further demonstrating the genetic substructure within the Mainland Japanese.
Genetic variation is a product of mutation, recombination and natural selection along with a complex history involving population subdivision, gene flow and changes in population size. Elucidating the evolutionary forces that shape genetic differences among populations is a major objective of evolutionary genetics. Recent advances in high-throughput technology enable genomic data to be obtained from samples at a population-based scale. Further, the growth in computational power has facilitated extensive efforts to develop intensive simulation-based approaches with the aim of analyzing such large-scale data and making inferences about population history. Approximate Bayesian computation (ABC) provides a quantitative way to assess the goodness-of-fit of complex models that are based on previous knowledge and to estimate the parameters of interest that produce the observed data. The practical advantage of ABC is the application of Bayesian inference to any model without the need to derive a likelihood function. ABC has rapidly become popular in ecology and evolutionary studies due to the contribution it has made to improving computational efficiency over the past decade. This review provides a brief overview of the background of ABC, including potential biases in estimation due to the assumptions and approximation involved, followed by an in-depth review of one of the recently developed ABCs, “kernel ABC,” with an explanation of how to overcome these biases. Finally, the application of kernel ABC to the inference of demographic history is summarized.
The acaulis2 (acl2) mutant of Arabidopsis thaliana shows a defect in flower stalk elongation. We identified the mutation point of acl2 by map-based cloning. The ACL2 locus is located within an approximately 320-kb region at around 100 map units on chromosome 1. One nucleotide substitution was detected in this region in the acl2 mutant, but no significant open reading frames were found around this mutation point. When wild-type DNA fragments containing the mutation point were introduced into acl2 mutant plants, some transgenic plants partially or almost completely recovered from the defect in flower stalk elongation. 3’-RACE experiments showed that bidirectional transcripts containing the acl2 mutation point were expressed, and the Plant MPSS database revealed that several small RNAs were produced from this region. Microarray analysis showed that transcription of many genes is activated in flower stalks of acl2 mutant plants. Overexpression of some of these genes caused a dwarf phenotype in wild-type plants. These results suggest the following novel mechanism for control of the elongation of flower stalks. Bidirectional non-coding RNAs are transcribed from the ACL2 locus, and small RNAs are generated from them in flower stalks. These small RNAs repress the transcription of a set of genes whose expression represses flower stalk elongation, and flower stalks are therefore fully elongated.
Real-time quantitative RT-PCR (qRT-PCR) is the most commonly used method for accurately detecting gene expression patterns. As part of qRT-PCR analysis, normalization of the data requires internal control gene(s) that display uniform expression under different biological conditions. However, no invariable internal control gene exists, and therefore more than one reference gene is needed to normalize RT-PCR results. In this study, we assessed the expression of eight candidate internal control genes, namely 18S ribosomal RNA (18S rRNA), elongation factor-1alpha, β-Actin, E2 ubiquitin-conjugating enzyme, β-Tubulin (TUB), ACTIN2, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and Msc27 of unknown function, in a diverse set of 16 alfalfa (Medicago sativa) samples representing different tissues and abiotic stress challenges, using geNorm and BestKeeper software. The results revealed that the eight candidate genes are inconsistently expressed under different experimental conditions. Msc27 and 18S rRNA are suitable reference genes for comparing different tissue types. Under different abscisic acid and NaCl conditions, three reference genes are necessary. Finally, GAPDH, TUB and β-Actin are unsuitable for normalization of qRT-PCR data under these given conditions in alfalfa. The relative expression level of MsWRKY33 was analyzed using selected reference genes. These results provide an experimental guideline for future research on gene expression in alfalfa using qRT-PCR.
In rice (Oryza sativa), floral organs develop in the spikelet, an inflorescence unit unique to grass species. The floral organs, such as carpels, stamens and lodicules, are enclosed by two spikelet organs, the palea and lemma. The number of floral organs is genetically regulated. Mutations in the FLORAL ORGAN NUMBER (FON) genes cause an increase in the number of carpels and stamens due to an enlargement of the floral meristem. The spikelet organs, such as lemma and palea, are less affected in the fon mutants. We found a mutant, fickle spikelet1 (fsp1), that displayed an increased number not only of floral organs but also of spikelet organs. Because the fsp1 spikelets showed a pleiotropic phenotype, we classified them into four types. The expressivity of the fsp1 phenotype varied from plant to plant, and also from panicle to panicle within a single plant. In addition, the frequency of each fsp1 spikelet type also varied considerably among plants and among panicles within a plant. When the fsp1 mutants were grown in a growth chamber, an extra abnormality, namely a defect in pollen development, was observed. Furthermore, the expressivity of the mutant phenotype increased dramatically in mutant plants grown in a growth chamber. Thus, the expressivity of the fsp1 phenotype seems to be strongly influenced by environmental conditions.