Mapping quantitative trait loci in selected breeding populations: A segregation distortion approach

Quantitative trait locus (QTL) mapping is often conducted in line-crossing experiments where a sample of individuals is randomly selected from a pool of all potential progeny. QTLs detected from such an experiment are important for us to understand the genetic mechanisms governing a complex trait, but may not be directly relevant to plant breeding if they are not detected from the breeding population where selection is targeting for. QTLs segregating in one population may not necessarily segregate in another population. To facilitate marker-assisted selection, QTLs must be detected from the very population which the selection is targeting. However, selected breeding populations often have depleted genetic variation with small population sizes, resulting in low power in detecting useful QTLs. On the other hand, if selection is effective, loci controlling the selected trait will deviate from the expected Mendelian segregation ratio. In this study, we proposed to detect QTLs in selected breeding populations via the detection of marker segregation distortion in either a single population or multiple populations using the same selection scheme. Simulation studies showed that QTL can be detected in strong selected populations with selected population sizes as small as 25 plants. We applied the new method to detect QTLs in two breeding populations of rice selected for high grain yield. Seven QTLs were identified, four of which have been validated in advanced generations in a follow-up study. Cloned genes in the vicinity of the four QTLs were also reported in the literatures. This mapping-by-selection approach provides a new avenue for breeders to improve breeding progress. The new method can be applied to breeding programs not only in rice but also in other agricultural species including crops, trees and animals.     

Glutathione S-transferase M1 and T1 polymorphisms in Brazilian African descendants

The glutathione S-transferase gene family has an important role in the biotransformation and detoxification of different xenobiotics and endogenous compounds. Two polymorphic genes of this family, GSTM1 and GSTT1, present null alleles that consequently do not produce the respective enzyme when the genotype is homozygous. These polymorphisms are also interesting for population dynamics studies because they have great frequency variations among different ethnic groups and have been reported worldwide. The distribution of these alleles in urban and Amerindian populations in Brazil has been described, but none of those studies reported on African-descended rural populations. The aim of this study was to analyze the genotype frequency distribution of the GSTM1 and GSTT1 null alleles in an urban sample from the Federal District (n = 91) and in four semi-isolated African-descended populations: Mocambo (n = 55), Rio das R?s (n = 117), Riacho de Sacutiaba (n = 34), and Kalunga (n = 68). The GSTM1 and GSTT1 null genotype frequencies in these populations range from 17% to 35% for GSTM1 and from 22% to 44% for GSTT1. These values are similar to those described in other African and African-descended populations. Despite this range, there is no distribution difference among the analyzed populations. Combined GSTM1 and GSTT1 null genotype frequencies range from 6% to 13% and are similar to European-derived populations, suggesting admixture with this ethnic group. This can be interpreted as a European contribution to these African-descended populations. Regarding the urban population in the Federal District, our results suggest an important African and European contribution.     

Solutions for PCR,cloning and sequencing errors in population genetic analysis

PCR and sequencing artefacts can seriously bias population genetic analyses, particularly of populations with low genetic variation such as endangered vertebrate populations. Here, we estimate the error rates, discuss their population genetics implications, and propose a simple detection method that helps to reduce the risk of accepting such errors. We study the major histocompatibility complex (MHC) class IIB of guppies, Poecilia reticulata and find that PCR base misincorporations inflate the apparent sequence diversity. When analysing neutral genes, such bias can inflate estimates of effective population size. Previously suggested protocols for identifying genuine alleles are unlikely to exclude all sequencing errors, or they ignore genuine sequence diversity. We present a novel and statistically robust method that reduces the likelihood of accepting PCR artefacts as genuine alleles, and which minimises the necessity of repeated genotyping. Our method identifies sequences that are unlikely to be a PCR artefact, and which need to be independently confirmed through additional PCR of the same template DNA. The proposed methods are recommended particularly for population genetic studies that involve multi-template DNA and in studies on genes with low genetic diversity.     

A sensitive and specific blocking ELISA for the detection of rabbit calicivirus RCV-A1 antibodies

ABSTRACT: BACKGROUND: Antibodies to non-pathogenic rabbit caliciviruses (RCVs) cross-react in serological tests for rabbit hemorrhagic disease virus (RHDV) and vice versa, making epidemiological studies very difficult where both viruses occur. It is important to understand the distribution and interaction of the two viruses because the highly pathogenic RHDV has been used as a biocontrol agent for wild rabbits in Australia and New Zealand for the past 17 years. The presence of the benign RCV Australia 1 (RCV-A1) is considered a key factor for the failure of RHDV mediated rabbit control in cooler, wetter areas of Australia. RESULTS: A highly sensitive and specific blocking ELISA was developed for the detection of RCV-A1 antibodies. When sera from rabbits with a known infection history for either RCV-A1 or RHDV were tested, this assay showed 100% sensitivity and no cross-reactivity with RHDV sera (100% specificity). CONCLUSIONS: This new ELISA not only allows the detection of RCV-A1 at a population level, but also permits the serological status of individual rabbits to be determined more reliably than previously described methods. This robust and simple to perform assay is therefore the tool of choice for studying RCV-A1 epidemiology in Australian wild rabbit populations.     

Utility of EST-derived SSRs as population genetics markers in a beetle

Microsatellite, or simple sequence repeat (SSR), loci can be identified by mining expressed sequence tag (EST) databases, and where these are available, marker development time and expense can be decreased considerably over conventional strategies of probing the entire genome. However, it is unclear whether they provide information on population structure similar to that generated by anonymous genomic SSRs. We performed comparative population genetic analyses between EST-derived SSRs (EST-SSRs) and anonymous SSRs developed from genomic DNA for the same set of populations of the insect Diabrotica virgifera, a beetle in the family Chrysomelidae. Compared with noncoding, nontranscribed regions, EST-SSRs were generally less polymorphic but had reduced occurrence of null alleles and greater cross-species amplification. Neutrality tests suggested the loci were not under positive selection. Across all populations and all loci, the genomic and EST-SSRs performed similarly in estimating genetic diversity, F(IS), F(ST), population assignment and exclusion tests, and detection of distinct populations. These findings, therefore, indicate that the EST-SSRs examined can be used with confidence in future genetic studies of Diabrotica populations and suggest that EST libraries can be added as a valuable source of markers for population genetics studies in insects and other animals.     

Breeding systems in the clam shrimp family Limnadiidae (Branchiopoda, Spinicaudata)

Abstract. Crustaceans in the class Branchiopoda exhibit a wide range of breeding systems, including dioecy (gonochorism), androdioecy, parthenogenesis, cyclic parthenogenesis, and hermaphroditism. The largest subgroup of the Branchiopods, the Diplostraca, is reported to encompass all five of these breeding systems. However, many of these reports are based primarily on simple observations of sex ratios in natural populations. Herein we report the beginnings of a more rigorous approach to breeding system determination in the Diplostraca, starting with the family Limnadiidae. We combine measurements of sex ratio, offspring rearings, and behavior to identify three breeding systems within the Limnadiidae: dioecy, androdioecy, and selfing hermaphroditism. To date, no instances of parthenogenetic reproduction have been identified in this family. Comparisons of breeding system determination via simple population sex ratios with our more controlled studies show that simple sex ratios can be useful when these sex ratios are ∼50% males (=dioecy) or 5–30% males (androdioecy). However, population sex ratios of 0–5% males or 35–45% males necessitate further investigation because estimates in these ranges cannot distinguish selfing hermaphroditism from androdioecy or androdioecy from dioecy, respectively. We conclude by noting that the genetic sex-determining system outlined for one of these limnadiid species, Eulimnadia texana , provides a parsimonious framework to describe the evolution of the three breeding systems observed within the Limnadiidae.     

DNA polymorphism in a worldwide sample of human X chromosomes

DNA sequence data from humans can provide insight into the history of modern humans and the genetic variability in human populations. We report here a study of human DNA sequence variation at an X-linked noncoding region of 10,346 bp. The sample consists of 62 X chromosomes from Africa, Europe, and Asia. Forty-four polymorphic sites were found among the 62 sequences, resulting in 23 different haplotypes. Statistical analyses of the data led to the following inferences. (1) There is strong evidence of human population expansion in the relatively recent past, and this population expansion has had a significant effect on the pattern of polymorphism at this locus. (2) Non-African populations were unlikely to have been derived from a very small number of African lineages. (3) There was considerable geographic subdivision in the ancient human population, which could be an important reason why many studies failed to detect population expansion. (4) The long-term effective population size of humans is between 12,000 and 15,000. And (5) a non-African specific variant was found at a frequency of 35% in non-Africans, an estimate supported by the genotyping of additional 80 non-African and 106 African X chromosomes. This variant could have arisen in Eurasia more than 140,000 years ago, predating the emergence of modern humans. Moreover, this haplotype and all other haplotypes coalesced to the most recent common ancestor of the sample, which was estimated to be older than 490,000 years. Therefore, this region may have a long history in Eurasia.     

Studies of wireworm populations

A method has been developed, and is here briefly described, by means of which all the wireworm larvae of all stages can be collected from soil samples. By use of that method, complete wireworm populations have been obtained from soil samples of three types, two of which provide large homogeneous populations for detailed study while the third gives information about the seasonal and spatial infestation of fields. These collections show that the wireworm population of English pasture land is on the average about three times as large as has been commonly supposed. Populations have been found ranging up to ten millions per acre in the top 12 in. of soil. In two pastures studied intensively throughout the year, the wireworm population has been found to consist of large numbers of small larvae, decreasing numbers of larger larvae, and comparatively few of the very large larvae that have usually been allowed to represent the population. Such a composition is shown to be characteristic of wireworm populations under old grass at all seasons of the year and in several fields in different parts of the country. This result suggests that in research on the wireworm problem it is desirable to take into consideration the whole wireworm population throughout the year, not merely the large larvae during the cropping season.     

微卫星标记在种群生物学研究中的应用

微卫星是以几个碱基 (一般为 1～ 6个 )为重复单位组成的简单的串联重复序列 ,具有丰度高、多态性高、共显性标记、选择中性、可自动检测等优点。本文着重介绍了微卫星在种群生物学研究中的应用。微卫星位点可以提供具高分辨率的遗传信息 ,这一特点使微卫星既适合于个体水平上的研究 ,又适合于种群水平上的研究。在个体水平上包括个体识别、交配系统和亲本分析、基因流等研究。微卫星是常用的个体识别手段 ,但在克隆植物遗传结构研究方面的应用还很有限 ;微卫星提高了交配系统和亲本分析、基因流等研究的准确性。在种群水平上微卫星可用于遗传结构、有效种群大小、种群的系统发育重建等研究。微卫星在很多物种 (包括珍稀物种 )的遗传结构研究中得到应用 ;利用微卫星标记确定有效种群大小、检测有效种群大小的波动可以促使我们正确理解种群遗传结构动态和种群进化过程 ;微卫星在种群的系统发育重建研究方面有很大的应用潜力。然而微卫星并不是研究所有问题的唯一选择。文中还讨论了在实际工作中应如何正确利用分子标记等问题     

Detection of highly polymorphic microsatellite loci in a species with little allozyme polymorphism

Microsatellite loci are regions of DNA containing tandem repeats of a short sequence motif; they occur abundantly in all eukaryotic genomes and have been shown to be a rich source of highly polymorphic genetic markers in humans and other mammals. These loci are particularly suitable for population studies because they can be relatively easily scored using a combination of polymerase chain reaction (PCR) amplification of each locus followed by electrophoresis to separate alleles. This paper details a method for finding these loci in any species. This method demonstrates that trinucleotide microsatellite loci are abundant and highly polymorphic in the social wasp Polistes annularis , whereas allozyme electrophoresis reveals very little polymorphism. The first six loci examined were all polymorphic with a mean observed heterozygosity of 0.62; in comparison average heterozygosity of 33 allozymes was 0.035. We suggest that this method can be used to detect variation where other methods have failed, making it an ideal tool for population and conservation geneticists who must deal with populations lacking other types of genetic variability.     

Whole‐genome sequencing of two North American Drosophila melanogaster populations reveals genetic differentiation and positive selection

The prevailing demographic model for Drosophila melanogaster suggests that the colonization of North America occurred very recently from a subset of European flies that rapidly expanded across the continent. This model implies a sudden population growth and range expansion consistent with very low or no population subdivision. As flies adapt to new environments, local adaptation events may be expected. To describe demographic and selective events during North American colonization, we have generated a data set of 35 individual whole‐genome sequences from inbred lines of D. melanogaster from a west coast US population (Winters, California, USA) and compared them with a public genome data set from Raleigh (Raleigh, North Carolina, USA). We analysed nuclear and mitochondrial genomes and described levels of variation and divergence within and between these two North American D. melanogaster populations. Both populations exhibit negative values of Tajima's D across the genome, a common signature of demographic expansion. We also detected a low but significant level of genome‐wide differentiation between the two populations, as well as multiple allele surfing events, which can be the result of gene drift in local subpopulations on the edge of an expansion wave. In contrast to this genome‐wide pattern, we uncovered a 50‐kilobase segment in chromosome arm 3L that showed all the hallmarks of a soft selective sweep in both populations. A comparison of allele frequencies within this divergent region among six populations from three continents allowed us to cluster these populations in two differentiated groups, providing evidence for the action of natural selection on a global scale.     

Matching strategies for genetic association studies in structured populations

Association studies in populations that are genetically heterogeneous can yield large numbers of spurious associations if population subgroups are unequally represented among cases and controls. This problem is particularly acute for studies involving pooled genotyping of very large numbers of single-nucleotide-polymorphism (SNP) markers, because most methods for analysis of association in structured populations require individual genotyping data. In this study, we present several strategies for matching case and control pools to have similar genetic compositions, based on ancestry information inferred from genotype data for approximately 300 SNPs tiled on an oligonucleotide-based genotyping array. We also discuss methods for measuring the impact of population stratification on an association study. Results for an admixed population and a phenotype strongly confounded with ancestry show that these simple matching strategies can effectively mitigate the impact of population stratification.     

Leveraging Genetic Variability across Populations for the Identification of Causal Variants

Genome-wide association studies have been performed extensively in the last few years, resulting in many new discoveries of genomic regions that are associated with complex traits. It is often the case that a SNP found to be associated with the condition is not the causal SNP, but a proxy to it as a result of linkage disequilibrium. For the identification of the actual causal SNP, fine-mapping follow-up is performed, either with the use of dense genotyping or by sequencing of the region. In either case, if the causal SNP is in high linkage disequilibrium with other SNPs, the fine-mapping procedure will require a very large sample size for the identification of the causal SNP. Here, we show that by leveraging genetic variability across populations, we significantly increase the localization success rate (LSR) for a causal SNP in a follow-up study that involves multiple populations as compared to a study that involves only one population. Thus, the average power for detection of the causal variant will be higher in a joint analysis than that in studies in which only one population is analyzed at a time. On the basis of this observation, we developed a framework to efficiently search for a follow-up study design: our framework searches for the best combination of populations from a pool of available populations to maximize the LSR for detection of a causal variant. This framework and its accompanying software can be used to considerably enhance the power of fine-mapping studies.     

A new method for detecting human recombination hotspots and its applications to the HapMap ENCODE data

Computational detection of recombination hotspots from population polymorphism data is important both for understanding the nature of recombination and for applications such as association studies. We propose a new method for this task based on a multiple-hotspot model and an (approximate) log-likelihood ratio test. A truncated, weighted pairwise log-likelihood is introduced and applied to the calculation of the log-likelihood ratio, and a forward-selection procedure is adopted to search for the optimal hotspot predictions. The method shows a relatively high power with a low false-positive rate in detecting multiple hotspots in simulation data and has a performance comparable to the best results of leading computational methods in experimental data for which recombination hotspots have been characterized by sperm-typing experiments. The method can be applied to both phased and unphased data directly, with a very fast computational speed. We applied the method to the 10 500-kb regions of the HapMap ENCODE data and found 172 hotspots among the three populations, with average hotspot width of 2.4 kb. By comparisons with the simulation data, we found some evidence that hotspots are not all identical across populations. The correlations between detected hotspots and several genomic characteristics were examined. In particular, we observed that DNaseI-hypersensitive sites are enriched in hotspots, suggesting the existence of human beta hotspots similar to those found in yeast.     

MNU-induced mutant pools and high performance TILLING enable finding of any gene mutation in rice

Mutant populations are indispensable genetic resources for functional genomics in all organisms. However, suitable rice mutant populations, induced either by chemicals or irradiation still have been rarely developed to date. To produce mutant pools and to launch a search system for rice gene mutations, we developed mutant populations of Oryza sativa japonica cv. Taichung 65, by treating single zygotic cells with N-methyl-N-nitrosourea (MNU). Mutagenesis in single zygotes can create mutations at a high frequency and rarely forms chimeric plants. A modified TILLING system using non-labeled primers and fast capillary gel electrophoresis was applied for high-throughput detection of single nucleotide substitution mutations. The mutation rate of an M₂ mutant population was calculated as 7.4 × 10⁻⁶ per nucleotide representing one mutation in every 135 kb genome sequence. One can expect 7.4 single nucleotide substitution mutations in every 1 kb of gene region when using 1,000 M₂ mutant lines. The mutations were very evenly distributed over the regions examined. These results indicate that our rice mutant population generated by MNU-mutagenesis could be a promising resource for identifying mutations in any gene of rice. The modified TILLING method also proved very efficient and convenient in screening the mutant population. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

A review of applications of environmental DNA for reptile conservation and management

Reptile populations are in decline globally, with total reptile abundance halving in the past half century, and approximately a fifth of species currently threatened with extinction. Research on reptile distributions, population trends, and trophic interactions can greatly improve the accuracy of conservation listings and planning for species recovery, but data deficiency is an impediment for many species. Environmental DNA (eDNA) can detect species and measure community diversity at diverse spatio‐temporal scales, and is especially useful for detection of elusive, cryptic, or rare species, making it potentially very valuable in herpetology. We aim to summarize the utility of eDNA as a tool for informing reptile conservation and management and discuss the benefits and limitations of this approach. A literature review was conducted to collect all studies that used eDNA and focus on reptile ecology, conservation, or management. Results of the literature search are summarized into key discussion points, and the review also draws on eDNA studies from other taxa to highlight methodological challenges and to identify future research directions. eDNA has had limited application to reptiles, relative to other vertebrate groups, and little use in regions with high species richness. eDNA techniques have been more successfully applied to aquatic reptiles than to terrestrial reptiles, and most (64%) of studies focused on aquatic habitats. Two of the four reptilian orders dominate the existing eDNA studies (56% Testudines, 49% Squamata, 5% Crocodilia, 0% Rhynchocephalia). Our review provides direction for the application of eDNA as an emerging tool in reptile ecology and conservation, especially when it can be paired with traditional monitoring approaches. Technologies associated with eDNA are rapidly advancing, and as techniques become more sensitive and accessible, we expect eDNA will be increasingly valuable for addressing key knowledge gaps for reptiles.     

Selecting subsets of genotyped experimental populations for phenotyping to maximize genetic diversity

Selective phenotyping is a way of capturing the benefits of large population sizes without the need to carry out large-scale phenotyping and hence is a cost-effective means of capturing information about gene–trait relationships within a population. The diversity within the sample gives an indication of the efficiency of this information capture; less diversity implies greater redundancy of the genetic information. Here, we propose a method to maximize genetic diversity within the selected samples. Our method is applicable to general experimental designs and robust to common problems such as missing data and dominant markers. In particular, we discuss its application to multi-parent advanced generation intercross (MAGIC) populations, where, although thousands of lines may be genotyped as a large population resource, only hundreds may need to be phenotyped for individual studies. Through simulation, we compare our method to simple random sampling and the minimum moment aberration method. While the gain in power over simple random sampling for all tested methods is not large, our method results in a much more diverse sample of genotypes. This diversity can be applied to improve fine mapping resolution once a QTL region has been detected. Further, when applied to two wheat datasets from doubled haploid and MAGIC progeny, our method detects known QTL for small sample sizes where other methods fail.     

RAPD markers on seed bulks efficiently assess the genetic diversity of a Brassica oleracea L. collection

 The concept of a core collection was elaborated to fit the necessity of optimizing the management, for both conservation and use, of genetic resources in sizeable collections. This approach requires an analysis of how the genetic variability is structured among the accessions. The large number of heterogeneous populations in our collection of Brassica oleracea makes genetic diversity studies based on plant-to-plant analysis impracticable. To overcome this limitation, the variability analysis by RAPD on seed bulks was investigated for its efficiency in assessing the structure of the genetic diversity of this collection. The optimal bulk size and the bulking or sampling variation were evaluated with bulks of different size and with replicated samples. A mixture of known genotypes was also used to characterise the band detection in bulks, and to compare the plant-to-plant and the bulk methods. Forty seeds were chosen to represent each population. In such a bulk, the detection of bands depended on the proportion of the genotype they were derived from in the mixture. Intense and frequent bands were detected in the bulk with a 15% detection limit. The observed bulking or sampling variation within populations was smaller than the variation between populations, leading to an efficient separation of populations with a clustering of all samples of the same population. The distances calculated from bulk data were highly correlated with the distances based on the plant-to-plant analysis. We demonstrated that RAPD on seed bulks can be used to describe the genetic diversity between populations. Received: 27 August 1998 / Accepted: 29 September 1998