Next-generation sequencing for understanding and accelerating crop domestication

Next generation Sequencing (NGS) provides a powerful tool for discovery of domestication genes in crop plants and their wild relatives. The accelerated domestication of new plant species as crops may be facilitated by this knowledge. Re-sequencing of domesticated genotypes can identify regions of low diversity associated with domestication. Species-specific data can be obtained from related wild species by whole-genome shot-gun sequencing. This sequence data can be used to design species specific polymerase chain reaction (PCR) primers. Sequencing of the products of PCR amplification of target genes can be used to explore genetic variation in large numbers of genes and gene families. Novel allelic variation in close or distant relatives can be characterized by NGS. Examples of recent applications of NGS to capture of genetic diversity for crop improvement include rice, sugarcane and Eucalypts. Populations of large numbers of individuals can be screened rapidly. NGS supports the rapid domestication of new plant species and the efficient identification and capture of novel genetic variation from related species.     

Allelematch: an R package for identifying unique multilocus genotypes where genotyping error and missing data may be present

We present allelematch, an R package, to automate the identification of unique multilocus genotypes in data sets where the number of individuals is unknown, and where genotyping error and missing data may be present. Such conditions commonly occur in noninvasive sampling protocols. Output from the software enables a comparison of unique genotypes and their matches, and facilitates the review of differences between profiles. The software has a variety of applications in molecular ecology, and may be valuable where a large number of samples must be processed, unique genotypes identified, and repeated observations made over space and time. We used simulations to assess the performance of allelematch and found that it can reliably and accurately determine the correct number of unique genotypes (± 3%) across a broad range of data set properties. We found that the software performs with highest accuracy when genotyping error is below 4%. The R package is available from the Comprehensive R Archive Network (http://cran.r-project.org/). Supplementary documentation and tutorials are provided.     

Predicting genotype environmental range from genome–environment associations

Genome–environment association methods aim to detect genetic markers associated with environmental variables. The detected associations are usually analysed separately to identify the genomic regions involved in local adaptation. However, a recent study suggests that single‐locus associations can be combined and used in a predictive way to estimate environmental variables for new individuals on the basis of their genotypes. Here, we introduce an original approach to predict the environmental range (values and upper and lower limits) of species genotypes from the genetic markers significantly associated with those environmental variables in an independent set of individuals. We illustrate this approach to predict aridity in a database constituted of 950 individuals of wild beets and 299 individuals of cultivated beets genotyped at 14,409 random single nucleotide polymorphisms (SNPs). We detected 66 alleles associated with aridity and used them to calculate the fraction (I) of aridity‐associated alleles in each individual. The fraction I correctly predicted the values of aridity in an independent validation set of wild individuals and was then used to predict aridity in the 299 cultivated individuals. Wild individuals had higher median values and a wider range of values of aridity than the cultivated individuals, suggesting that wild individuals have higher ability to resist to stress‐aridity conditions and could be used to improve the resistance of cultivated varieties to aridity.     

The genetic impact of demographic decline and reintroduction in the wild boar (Sus scrofa): a microsatellite analysis

The reintroduction of wild boar from central Europe after World War II has contributed substantially to the range expansion of this species in Italy, where indiscriminate hunting in earlier times resulted in extreme demographic reduction. However, the genetic impact of such processes is not well-understood. In this study, 105 individuals from Italian and Hungarian wild boar populations were characterized for nine autosomal microsatellite loci. The Hungarian samples, and two central Italian samples from protected areas (parks) where reintroduction is not documented, were assumed to be representative of the genetic composition of the source and the target populations in the reintroduction process, respectively. Animals hunted in the wild in the Florence area of Tuscany (Italy) were then studied to identify the effects of reintroduction. The results we obtained can be summarized as follows: (i) none of the populations analysed shows genetic evidence of demographic decline; (ii) the three parental populations from Italy and Hungary are genetically distinct; however, the low level of divergence appears in conflict with the naming of the Italian and the European subspecies (Sus scrofa majori and Sus scrofa scrofa, respectively); in addition, the Italian groups appear to be as divergent from each other as they are from the Hungarian population; (iii) most of the individuals hunted near Florence are genetically intermediate between the parental groups, suggesting that hybridization has occurred in this area, the average introgression of Hungarian genotypes is 13%, but approximately 45% of the genetic pool of these individuals can not be directly attributed to any of the parental populations we analysed; (iv) analysis of microsatellite loci, though in a limited number, is an important tool for estimating the genetic effect of reintroduction in the wild boar, and therefore for the development of conservation and management strategies for this species.     

Human phylogenetic relationships according to the D1S80 locus

By analyzing the allelic frequencies at the D1S80 locus in 43 human populations, we show that the locus is polymorphic globally and that it can be used to discriminate between major racial groups and subpopulations through phylogenetic analysis. Although the use of informative multiple loci generally provides more accurate phylogenetic relationships, in instances where time and/or target DNA availability is limited, D1S80 could provide useful data to discriminate between human groups. Also, knowledge of which loci independently provide accurate phylogenetic relationships, such as the D1S80, can be used to design more accurate multi-locus combinations. In addition, allele frequencies at the locus are reported, for the first time, for Bahamian individuals of African origin and for Chimila, Bari, and Navajo (Cañoncito Valley) native Americans. Allelic data was obtained using standard polymerase chain reaction (PCR) techniques. In the four new populations, 65 genotypes and 20 segregating alleles were observed. All populations conformed to Hardy-Weinberg expectations except the Chimila.     

An efficient method for screening faecal DNA genotypes and detecting new individuals and hybrids in the red wolf (<Emphasis Type="Italic">Canis rufus</Emphasis>) experimental population area

Previously, sequencing of mitochondrial DNA (mtDNA) from non-invasively collected faecal material (scat) has been used to help manage hybridization in the wild red wolf (Canis rufus) population. This method is limited by the maternal inheritance of mtDNA and the inability to obtain individual identification. Here, we optimize the use of nuclear DNA microsatellite markers on red wolf scat DNA to distinguish between individuals and detect hybrids. We develop a data filtering method in which scat genotypes are compared to known blood genotypes to reduce the number of PCR amplifications needed. We apply our data filtering method and the more conservative maximum likelihood ratio method (MLR) of Miller et al. (2002 Genetics 160:357–366) to a scat dataset previously screened for hybrids by sequencing of mtDNA. Using seven microsatellite loci, we obtained genotypes for 105 scats, which were matched to 17 individuals. The PCR amplification success rate was 50% and genotyping error rates ranged from 6.6% to 52.1% per locus. Our data filtering method produced comparable results to the MLR method, and decreased the time and cost of analysis by 25%. Analysis of this dataset using our data filtering method verified that no hybrid individuals were present in the Alligator River National Wildlife Refuge, North Carolina in 2000. Our results demonstrate that nuclear DNA microsatellite analysis of red wolf scats provides an efficient and accurate approach to screen for new individuals and hybrids.     

Using genetic markers to directly estimate male selection gradients

We present an analysis of Raphanus raphanistrum and simulations illustrating the utility of directly estimating male phenotypic selection gradients using genetic markers. The method offers a much more refined characterization of selection than attempting to assign paternity to individual progeny. Our analysis of R. raphanistrum reveals selection on remarkably fine features of floral morphology, including anther exsertion, that were opaque to previous approaches. The new results also undermine a previous conclusion that selection on wild radish floral morphology acts primarily through female fitness. Simulation results show that selection gradients on the order of beta = 0.1-0.2 can be readily detected with allozyme markers in moderate-sized (< 200 paternal individuals) populations. Highly polymorphic (e.g., microsatellite) markers will likely detect fine scale selection (beta < 0.1) in larger populations (> or = 400 individuals). Increased progeny sample size, by sampling either additional maternal families or more progeny per maternal parent, partly compensates for low exclusion probability. Increasing the number of possible fathers without changing progeny sample size decreases the ability to detect selection, especially at lower exclusion probabilities. Sampling only some male genotypes reduces the power to detect selection and biases (underestimates) the magnitude of the selection gradient estimate.     

BIOACOUSTIC PUBLICATIONS, 1987

The use of amplitudes to identify individuals has historically been ignored by bioacoustic researchers due to problems of attenuation. However, recent studies have shown that amplitudes encode identity in a variety of mammal species. Previously, individuality has been demonstrated in both fundamental frequency (F₀) and amplitude changes of captive Eastern wolf (Canis lupus lycaon) howls with 100% accuracy where attenuation of amplitude due to distance was controlled in a captive environment. In this study, we aim to determine whether both fundamental frequency and amplitude data collected from vocalizations of wild wolves recorded over unknown distances, in variable conditions and with different recording equipment, can still encode identity. We used a bespoke code, developed in Matlab, to extract simple scalar variables from 67 high-quality solo howls from 10 wild individuals and 112 chorus howls from another 109 individuals, including lower quality howls with wind or water noise. Principal component analysis (PCA) was carried out on the fundamental frequency and normalized amplitude of harmonic 1, yielding histogram-derived PCA values on which discriminant function analysis was applied. An accuracy of 100% was achieved when assigning solo howls to individuals, and for the chorus howls a best accuracy of 97.4% was achieved. We suggest that individual recognition using our new extraction and analysis methods involving fundamental frequency and amplitudes together can identify wild wolves with high accuracy, and that this method should be applied to surveys of individuals in capture–mark–recapture and presence–absence studies of canid species.     

ISSR fingerprinting of Coffea arabica throughout Ethiopia reveals high variability in wild populations and distinguishes them from landraces

Forests of SW Ethiopia constitute the native habitat of Coffea arabica and also the place where domestication of Arabica coffee started. Selection from wild populations has led to numerous landraces (farmer’s varieties) and cultivars. Inter-simple sequence repeats (ISSRs) were generated from a representative set of forest coffee populations and landraces across Ethiopia. For the broad diversity assessment, nine di- and tri-nucleotide ISSR primers were applied, as chosen from a total of 102 primers tested initially. Tetranucleotide ISSR primers differed in amplifying fingerprints that could hardly be analysed due to excessive variation. Tree building analysis (NJ, UPGMA) of 84 polymorphic loci amplified for 125 C. arabica individuals provided evidence for several groups of related genotypes occurring in certain geographical areas of Ethiopia and underscored the existence of wild coffee distinct from landraces. Landraces seem to have originated in different geographical areas of Ethiopia in a stepwise domestication process. While the overall geographical signal in the dataset was weak, analysis in a Bayesian framework using the admixture model with geographical priors in STRUCTURE recovered some genetic clustering. Based on Shannon’s diversity index, populations from Yayu (0.47) and Bonga (0.46) showed highest diversity, followed by individuals from Berhane Kontir (0.41). A likely scenario for the differentiation of C. arabica after an allopolyploidization event is that the hierarchical-geographical patterning of wild Coffea genotypes expected from stepwise range extension was obscured by recent or ancient gene flow. The diversity and geographical distribution of autochthonous C. arabica genotypes indicates the need for a multi-site in situ conservation approach.     

Hybridization versus conservation: are domestic cats threatening the genetic integrity of wildcats (Felis silvestris silvestris) in Iberian Peninsula?

Cross-breeding between wild and free-ranging domestic species is one of the main conservation problems for some threatened species. The situation of wildcats (Felis silvestris silvestris) in Europe is a good example of this critical phenomenon. Extensive hybridization was described in Hungary and Scotland, contrasting with occasional interbreeding in Italy and Germany. First analyses in Portugal revealed a clear genetic differentiation between wild and domestic cats; however, four hybrids were detected. Here, we extended the approach to Iberian Peninsula using multivariate and Bayesian analyses of multilocus genotypes for 44 Portuguese wildcats, 31 Spanish wildcats and 109 domestic cats. Globally, wild and domestic cats were significantly differentiated (FST=0.20, p<0.001) and clustered into two discrete groups. Diverse clustering methods and assignment criteria identified an additional hybrid in Portugal, performing a total of five admixed individuals. The power of admixture analyses was assessed by simulating hybrid genotypes, which revealed that used microsatellites were able to detect 100, 91 and 85% of first-generation hybrids, second-generation genotypes and backcrosses, respectively. These findings suggest that the true proportion of admixture can be higher than the value estimated in this study and that the improvement of genetic tools for hybrids detection is crucial for wildcat conservation.     

Genetic relationship among wild,landraces and cultivars of hazelnut (Corylus avellana) from Portugal revealed through ISSR and AFLP markers

The genus Corylus, a member of the birch family Betulaceae, includes several species that are widely distributed throughout temperate regions of the Northern Hemisphere. This study assesses the genetic diversity in 26 international cultivars and 32 accessions of Corylus avellana L. from Portugal: 13 wild genotypes and 19 landraces. The genetic relationships among the 58 hazelnuts (Corylus avellana L.) were analyzed using inter simple sequence repeat (ISSR) and amplified fragment length polymorphism (AFLP) markers. Eighteen ISSR primers and seven AFLP primer pairs generated a total of 570 unambiguous and repeatable bands, respectively, from which 541 (95.03 %) were polymorphic for both markers. Genetic similarity index values ranged from 0.239 for wild types and cultivars to 0.143 for landraces and wild types. The genetic relationships were presented as a Neighbor-Joining method dendrogram and a two-dimensional principal coordinate analysis (PCoA) plot. The Neighbor-Joining dendrogram showed three main clusters, and the PCoA analysis has shown to be congruent with the hierarchical analysis. Bayesian analysis clustered all individuals into three groups showing a good separation among wild genotypes, landraces and cultivars. The genetic diversity found on wild genotypes and Portuguese landraces may provide relevant information for the diversity conservation and it will be useful in breeding programs and to identify local selections for preservation.     

Quantifying Population Genetic Differentiation from Next-Generation Sequencing Data

Over the past few years, new high-throughput DNA sequencing technologies have dramatically increased speed and reduced sequencing costs. However, the use of these sequencing technologies is often challenged by errors and biases associated with the bioinformatical methods used for analyzing the data. In particular, the use of naïve methods to identify polymorphic sites and infer genotypes can inflate downstream analyses. Recently, explicit modeling of genotype probability distributions has been proposed as a method for taking genotype call uncertainty into account. Based on this idea, we propose a novel method for quantifying population genetic differentiation from next-generation sequencing data. In addition, we present a strategy for investigating population structure via principal components analysis. Through extensive simulations, we compare the new method herein proposed to approaches based on genotype calling and demonstrate a marked improvement in estimation accuracy for a wide range of conditions. We apply the method to a large-scale genomic data set of domesticated and wild silkworms sequenced at low coverage. We find that we can infer the fine-scale genetic structure of the sampled individuals, suggesting that employing this new method is useful for investigating the genetic relationships of populations sampled at low coverage.     

The development of SSR markers by a new method in plants and their application to gene flow studies in azuki bean [<Emphasis Type="Italic">Vigna angularis</Emphasis> (Willd.) Ohwi &; Ohashi]

To gain a better understanding of wild and weedy azuki population structures in relation to the cultigens we have developed simple sequence repeat (SSR) markers based on a new methodology for plant material. In the azuki bean genome, the number of (AG)_n and (AC)_n motif loci per haploid genome has been estimated to be 3,500 and 2,100, respectively, indicating that (AG)_n motifs are a rich source of markers. We constructed a (AG)_n-SSR-enriched library in azuki bean in order to obtain a comprehensive range of SSR markers efficiently. The method applied in this study resulted in a 116-fold enrichment over the non-enriched genomic library, with a high percentage (98%) of successful single-locus amplification by the primer pairs designed. Consequently, this method can be applied to construct SSR-enriched libraries suitable for large-scale sequencing. We obtained 255 unique sequences from an (AG)_n-enriched library for azuki bean. Fifty primer pairs were designed and screened against five populations of wild azuki bean. Among these five populations, one population from Bato town, Tochigi prefecture, Japan, showed greater polymorphism using these primers than the others and was therefore chosen for the in-depth study. The genotypes of 20 individuals were investigated using eight of the SSR primers developed. The genetic relationships among individuals revealed a complex spatial pattern of population structure. Although azuki bean is considered to be a predominantly self-pollinating species, 3 of the 20 individuals tested in the population showed heterozygous genotypes, indicating outcrossing. Allele size and DNA sequence in each of the 20 individuals were compared with those of landraces and released cultivars of azuki bean. Plants in part of the population had many alleles of the same size and with the same sequence as those in cultivated azuki bean, suggesting that gene flow from the cultigen to wild plants has occurred in this population. Unintentional transgene escape from azuki could therefore occur when transgenic azuki is grown in areas where its wild and weedy relatives occur. The approach used here could be applied to biosafety monitoring of transgenic azuki bean.Communicated by C. MöllersX.W. Wang and A. Kaga contributed equally to the results presented in this paper.     

Moving beyond heritability in the search for coral adaptive potential

Global environmental change is happening at unprecedented rates. Coral reefs are among the ecosystems most threatened by global change. For wild populations to persist, they must adapt. Knowledge shortfalls about corals' complex ecological and evolutionary dynamics, however, stymie predictions about potential adaptation to future conditions. Here, we review adaptation through the lens of quantitative genetics. We argue that coral adaptation studies can benefit greatly from “wild” quantitative genetic methods, where traits are studied in wild populations undergoing natural selection, genomic relationship matrices can replace breeding experiments, and analyses can be extended to examine genetic constraints among traits. In addition, individuals with advantageous genotypes for anticipated future conditions can be identified. Finally, genomic genotyping supports simultaneous consideration of how genetic diversity is arrayed across geographic and environmental distances, providing greater context for predictions of phenotypic evolution at a metapopulation scale.     

Mitochondrial and nuclear DNA analyses reveal pronounced genetic structuring in Tunisian wild boar <Emphasis Type="Italic">Sus scrofa</Emphasis>

We analysed 74 wild boars from Tunisia with respect to patterns of genetic differentiation and diversity based on sequences of the mitochondrial control region and genotypes at eight nuclear microsatellite loci. Analysis of molecular variance for both marker systems and Bayesian structure analysis of our microsatellite data revealed a clear break between northern and southern populations. Southern wild boar were monomorphic for one of three mtDNA haplotypes; the other two (one of which only occurred in three individuals) were confined to the north. A comparison with published sequences showed all three haplotypes to belong to the major European clade E1. Microsatellite diversity was similar to that found in earlier studies of wild boar (expected heterozygosity of 0.695 and 0.597 for the north and south, respectively). Contrary to the mtDNA results, we did not find unequivocal evidence of a bottleneck in Tunisian wild boar based on our microsatellite data. The clear distinction between northern and southern populations may be due to an Algerian origin of the southern animals.     

Molecular tracking of mountain lions in the Yosemite valley region in California: genetic analysis using microsatellites and faecal DNA

Twelve microsatellite loci were characterized in California mountain lions (Puma concolor) and sufficient polymorphism was found to uniquely genotype 62 animals sampled at necropsy. Microsatellite genotypes obtained using mountain lion faecal DNA matched those from muscle for all of 15 individuals examined. DNA from potential prey species and animals whose faeces could be misidentified as mountain lion faeces were reliably distinguished from mountain lions using this microsatellite panel. In a field application of this technique, 32 faecal samples were collected from hiking trails in the Yosemite Valley region where seven mountain lions previously had been captured, sampled, and released. Twelve samples yielded characteristic mountain lion genotypes, three displayed bobcat-type genotypes, and 17 did not amplify. The genotype of one of the 12 mountain lion faecal samples was identical to one of the mountain lions that previously had been captured. Three of the 12 faecal samples yielded identical genotypes, and eight new genotypes were detected in the remaining samples. This analysis provided a minimum estimate of 16 mountain lions (seven identified by capture and nine identified by faecal DNA) living in or travelling through Yosemite Valley from March 1997 to August 1998. Match probabilities (probabilities that identical DNA genotypes would be drawn at random a second time from the population) indicated that the samples with identical genotypes probably came from the same mountain lion. Our results demonstrate that faecal DNA analysis is an effective method for detecting and identifying individual mountain lions.     

Family-based association tests for genomewide association scans

With millions of single-nucleotide polymorphisms (SNPs) identified and characterized, genomewide association studies have begun to identify susceptibility genes for complex traits and diseases. These studies involve the characterization and analysis of very-high-resolution SNP genotype data for hundreds or thousands of individuals. We describe a computationally efficient approach to testing association between SNPs and quantitative phenotypes, which can be applied to whole-genome association scans. In addition to observed genotypes, our approach allows estimation of missing genotypes, resulting in substantial increases in power when genotyping resources are limited. We estimate missing genotypes probabilistically using the Lander-Green or Elston-Stewart algorithms and combine high-resolution SNP genotypes for a subset of individuals in each pedigree with sparser marker data for the remaining individuals. We show that power is increased whenever phenotype information for ungenotyped individuals is included in analyses and that high-density genotyping of just three carefully selected individuals in a nuclear family can recover >90% of the information available if every individual were genotyped, for a fraction of the cost and experimental effort. To aid in study design, we evaluate the power of strategies that genotype different subsets of individuals in each pedigree and make recommendations about which individuals should be genotyped at a high density. To illustrate our method, we performed genomewide association analysis for 27 gene-expression phenotypes in 3-generation families (Centre d'Etude du Polymorphisme Humain pedigrees), in which genotypes for ~860,000 SNPs in 90 grandparents and parents are complemented by genotypes for ~6,700 SNPs in a total of 168 individuals. In addition to increasing the evidence of association at 15 previously identified cis-acting associated alleles, our genotype-inference algorithm allowed us to identify associated alleles at 4 cis-acting loci that were missed when analysis was restricted to individuals with the high-density SNP data. Our genotype-inference algorithm and the proposed association tests are implemented in software that is available for free.     

Close relatives in population samples: Evaluation of the consequences for genetic stock identification

Determining the origin of individuals in mixed population samples is key in many ecological, conservation and management contexts. Genetic data can be analyzed using genetic stock identification (GSI), where the origin of single individuals is determined using Individual Assignment (IA) and population proportions are estimated with Mixed Stock Analysis (MSA). In such analyses, allele frequencies in a reference baseline are required. Unknown individuals or mixture proportions are assigned to source populations based on the likelihood that their multilocus genotypes occur in a particular baseline sample. Representative sampling of populations included in a baseline is important when designing and performing GSI. Here, we investigate the effects of family sampling on GSI, using both simulated and empirical genotypes for Atlantic salmon (Salmo salar). We show that nonrepresentative sampling leading to inclusion of close relatives in a reference baseline may introduce bias in estimated proportions of contributing populations in a mixed sample, and increases the amount of incorrectly assigned individual fish. Simulated data further show that the induced bias increases with increasing family structure, but that it can be partly mitigated by increased baseline population sample sizes. Results from standard accuracy tests of GSI (using only a reference baseline and/or self‐assignment) gave a false and elevated indication of the baseline power and accuracy to identify stock proportions and individuals. These findings suggest that family structure in baseline population samples should be quantified and its consequences evaluated, before carrying out GSI.     

富集优势基因型的后备亲本筛选以及相关分子标记的遗传效应分析

选取黄河鲤新品系亲本和子代共450尾,5对微卫星引物和4个基因区段扩增引物开展基因型检测,并检测它们与体重的关联性以及分析相应的遗传效应。结果显示:Koi42和4个SNPs位点对体重有显著的影响,获得具有超过富集2个优势基因型的候选亲本共13尾,富集优势分子标记基因型的候选亲本生长性能优势明显。通过多元逐步回归分析,利用AIC最佳模型筛选到COⅠ626、D-Loop253和Koi42共3个位点,发现Koi42贡献率较大,经Fisher精确性检验,发现其与性别存在关联,其加性效应接近显著水平（P < 0.05）。检测的多个上位效应组分中,仅有D-Loop253和Koi42的加性效应间的互作达到显著水平。对遗传方差组分进行剖分发现,加性方差占11.4%,两个位点的加性效应构成的上位效应占到77.5%,因此这3个分子标记对体重的影响主要以上位效应为主,而且是两两加性效应的占比较大,可以推断出D-Loop 253和Koi42两个分子标记的上位效应起主要作用。综上所述结果提示Koi42及与其有互作的D-Loop253可用于黄河鲤新品系的标记辅助选择,可以开展多个分子标记的富集选择。