What can patterns of differentiation across plant genomes tell us about adaptation and speciation?

Genome scans have become a common approach to identify genomic signatures of natural selection and reproductive isolation, as well as the genomic bases of ecologically relevant phenotypes, based on patterns of polymorphism and differentiation among populations or species. Here, we review the results of studies taking genome scan approaches in plants, consider the patterns of genomic differentiation documented and their possible causes, discuss the results in light of recent models of genomic differentiation during divergent adaptation and speciation, and consider assumptions and caveats in their interpretation. We find that genomic regions of high divergence generally appear quite small in comparisons of both closely and more distantly related populations, and for the most part, these differentiated regions are spread throughout the genome rather than strongly clustered. Thus, the genome scan approach appears well-suited for identifying genomic regions or even candidate genes that underlie adaptive divergence and/or reproductive barriers. We consider other methodologies that may be used in conjunction with genome scan approaches, and suggest further developments that would be valuable. These include broader use of sequence-based markers of known genomic location, greater attention to sampling strategies to make use of parallel environmental or phenotypic transitions, more integration with approaches such as quantitative trait loci mapping and measures of gene flow across the genome, and additional theoretical and simulation work on processes related to divergent adaptation and speciation.     

Characterization of a divergent chromosome region in the willow warbler Phylloscopus trochilus using avian genomic resources

Genome scans have made it possible to find outlier markers thought to have been influenced by divergent selection in almost any wild population. However, the lack of genomic information in nonmodel species often makes it difficult to associate these markers with certain genes or chromosome regions. Furthermore, the extent of linkage disequilibrium (LD) in the genome will determine the density of markers required to identify the genes under selection. In this study, we investigated a chromosome region in the willow warbler Phylloscopus trochilus surrounding a single marker previously identified in a genome scan. We first located the marker in the assembled genome of another species, the zebra finch Taeniopygia guttata, and amplified surrounding sequences in Fennoscandian willow warblers. Within an investigated chromosome region of 7.3 Mb as mapped to the zebra finch genome, we observed elevated genetic differentiation between a southern and a northern population across a 2.5-Mb interval comprising numerous coding genes. Within the southern and northern populations, higher values of LD were mostly found between SNPs within the same locus, but extended across distantly situated loci when the analyses were restricted to sampling sites showing intermediate allele frequencies of southern and northern alleles. Our study shows that cross-species genome information is a useful resource to obtain candidate sequences adjacent to outlier markers in nonmodel species.     

A first generation physical map of the medaka genome in BACs essential for positional cloning and clone-by-clone based genomic sequencing

In order to realize the full potential of the medaka as a model system for developmental biology and genetics, characterized genomic resources need to be established, culminating in the sequence of the medaka genome. To facilitate the map-based cloning of genes underlying induced mutations and to provide templates for clone-based genomic sequencing, we have created a first-generation physical map of the medaka genome in bacterial artificial chromosome (BAC) clones. In particular, we exploited the synteny to the closely related genome of the pufferfish, Takifugu rubripes, by marker content mapping. As a first step, we clustered 103,144 public medaka EST sequences to obtain a set of 21,121 non-redundant sequence entities. Avoiding oversampling of gene-dense regions, 11,254 of EST clusters were successfully matched against the draft sequence of the fugu genome, and 2363 genes were selected for the BAC map project. We designed 35mer oligonucleotide probes from the selected genes and hybridized them against 64,500 BAC clones of strains Cab and Hd-rR, representing 14-fold coverage of the medaka genome. Our data set is further supplemented with 437 results generated from PCR-amplified inserts of medaka cDNA clones and BAC end-fragment markers. Our current, edited, first generation medaka BAC map consists of 902 map segments that cover about 74% of the medaka genome. The map contains 2721 markers. Of these, 2534 are from expressed sequences, equivalent to a non-redundant set of 2328 loci. The 934 markers (724 different) are anchored to the medaka genetic map. Thus, genetic map assignments provide immediate access to underlying clones and contigs, simplifying molecular access to candidate gene regions and their characterization.     

Breaking RAD: an evaluation of the utility of restriction site‐associated DNA sequencing for genome scans of adaptation

Understanding how and why populations evolve is of fundamental importance to molecular ecology. Restriction site‐associated DNA sequencing (RADseq), a popular reduced representation method, has ushered in a new era of genome‐scale research for assessing population structure, hybridization, demographic history, phylogeography and migration. RADseq has also been widely used to conduct genome scans to detect loci involved in adaptive divergence among natural populations. Here, we examine the capacity of those RADseq‐based genome scan studies to detect loci involved in local adaptation. To understand what proportion of the genome is missed by RADseq studies, we developed a simple model using different numbers of RAD‐tags, genome sizes and extents of linkage disequilibrium (length of haplotype blocks). Under the best‐case modelling scenario, we found that RADseq using six‐ or eight‐base pair cutting restriction enzymes would fail to sample many regions of the genome, especially for species with short linkage disequilibrium. We then surveyed recent studies that have used RADseq for genome scans and found that the median density of markers across these studies was 4.08 RAD‐tag markers per megabase (one marker per 245 kb). The length of linkage disequilibrium for many species is one to three orders of magnitude less than density of the typical recent RADseq study. Thus, we conclude that genome scans based on RADseq data alone, while useful for studies of neutral genetic variation and genetic population structure, will likely miss many loci under selection in studies of local adaptation.     

Genome scans reveal candidate regions involved in the adaptation to host plant in the pea aphid complex

A major goal in evolutionary biology is to uncover the genetic basis of adaptation. Divergent selection exerted on ecological traits may result in adaptive population differentiation and reproductive isolation and affect differentially the level of genetic divergence along the genome. Genome‐wide scan of large sets of individuals from multiple populations is a powerful approach to identify loci or genomic regions under ecologically divergent selection. Here, we focused on the pea aphid, a species complex of divergent host races, to explore the organization of the genomic divergence associated with host plant adaptation and ecological speciation. We analysed 390 microsatellite markers located at variable distances from predicted genes in replicate samples of sympatric populations of the pea aphid collected on alfalfa, red clover and pea, which correspond to three common host‐adapted races reported in this species complex. Using a method that accounts for the hierarchical structure of our data set, we found a set of 11 outlier loci that show higher genetic differentiation between host races than expected under the null hypothesis of neutral evolution. Two of the outliers are close to olfactory receptor genes and three other nearby genes encoding salivary proteins. The remaining outliers are located in regions with genes of unknown functions, or which functions are unlikely to be involved in interactions with the host plant. This study reveals genetic signatures of divergent selection across the genome and provides an inventory of candidate genes responsible for plant specialization in the pea aphid, thereby setting the stage for future functional studies.     

The Human Obesity Gene Map: The 2003 Update

This is the tenth update of the human obesity gene map, incorporating published results up to the end of October 2003 and continuing the previous format. Evidence from single‐gene mutation obesity cases, Mendelian disorders exhibiting obesity as a clinical feature, quantitative trait loci (QTLs) from human genome‐wide scans and animal crossbreeding experiments, and association and linkage studies with candidate genes and other markers is reviewed. Transgenic and knockout murine models relevant to obesity are also incorporated (N = 55). As of October 2003, 41 Mendelian syndromes relevant to human obesity have been mapped to a genomic region, and causal genes or strong candidates have been identified for most of these syndromes. QTLs reported from animal models currently number 183. There are 208 human QTLs for obesity phenotypes from genome‐wide scans and candidate regions in targeted studies. A total of 35 genomic regions harbor QTLs replicated among two to five studies. Attempts to relate DNA sequence variation in specific genes to obesity phenotypes continue to grow, with 272 studies reporting positive associations with 90 candidate genes. Fifteen such candidate genes are supported by at least five positive studies. The obesity gene map shows putative loci on all chromosomes except Y. Overall, more than 430 genes, markers, and chromosomal regions have been associated or linked with human obesity phenotypes. The electronic version of the map with links to useful sites can be found at http:obesitygene.pbrc.edu .     

The coupling hypothesis: why genome scans may fail to map local adaptation genes

Genomic scans of multiple populations often reveal marker loci with greatly increased differentiation between populations. Often this differentiation coincides in space with contrasts in ecological factors, forming a genetic-environment association (GEA). GEAs imply a role for local adaptation, and so it is tempting to conclude that the strongly differentiated markers are themselves under ecologically based divergent selection, or are closely linked to loci under such selection. Here, we highlight an alternative and neglected explanation: intrinsic (i.e. environment-independent) pre- or post-zygotic genetic incompatibilities rather than local adaptation can be responsible for increased differentiation. Intrinsic genetic incompatibilities create endogenous barriers to gene flow, also known as tension zones, whose location can shift over time. However, tension zones have a tendency to become trapped by, and therefore to coincide with, exogenous barriers due to ecological selection. This coupling of endogenous and exogenous barriers can occur easily in spatially subdivided populations, even if the loci involved are unlinked. The result is that local adaptation explains where genetic breaks are positioned, but not necessarily their existence, which can be best explained by endogenous incompatibilities. More precisely, we show that (i) the coupling of endogenous and exogenous barriers can easily occur even when ecological selection is weak; (ii) when environmental heterogeneity is fine-grained, GEAs can emerge at incompatibility loci, but only locally, in places where habitats and gene pools are sufficiently intermingled to maintain linkage disequilibria between genetic incompatibilities, local-adaptation genes and neutral loci. Furthermore, the association between the locally adapted and intrinsically incompatible alleles (i.e. the sign of linkage disequilibrium between endogenous and exogenous loci) is arbitrary and can form in either direction. Reviewing results from the literature, we find that many predictions of our model are supported, including endogenous genetic barriers that coincide with environmental boundaries, local GEA in mosaic hybrid zones, and inverted or modified GEAs at distant locations. We argue that endogenous genetic barriers are often more likely than local adaptation to explain the majority of Fst-outlying loci observed in genome scan approaches - even when these are correlated to environmental variables.     

Population genomics and speciation

The process of speciation begins with genomically-localised barriers to gene exchange associated with loci for local adaptation, intrinsic incompatibility or assortative mating. The barrier then spreads until reproductive isolation influences the whole genome. The population genomics approach can be used to identify regions of reduced gene flow by detecting loci with greater differentiation than expected from the average across many loci. Recently, this approach has been used in several systems. I review these studies, concentrating on the robustness of the approach and the methods available to go beyond the simple identification of differentiated markers. Population genomics has already contributed significantly to understanding the balance between gene flow and selection during the evolution of reproductive isolation and has great future potential both in genome species and in non-model organisms.     

High degree of genetic differentiation in marine three‐spined sticklebacks (Gasterosteus aculeatus)

Populations of widespread marine organisms are typically characterized by a low degree of genetic differentiation in neutral genetic markers, but much less is known about differentiation in genes whose functional roles are associated with specific selection regimes. To uncover possible adaptive population divergence and heterogeneous genomic differentiation in marine three‐spined sticklebacks (Gasterosteus aculeatus), we used a candidate gene‐based genome‐scan approach to analyse variability in 138 microsatellite loci located within/close to (<6 kb) functionally important genes in samples collected from ten geographic locations. The degree of genetic differentiation in markers classified as neutral or under balancing selection—as determined with several outlier detection methods—was low (F_ST = 0.033 or 0.011, respectively), whereas average F_ST for directionally selected markers was significantly higher (F_ST = 0.097). Clustering analyses provided support for genomic and geographic heterogeneity in selection: six genetic clusters were identified based on allele frequency differences in the directionally selected loci, whereas four were identified with the neutral loci. Allelic variation in several loci exhibited significant associations with environmental variables, supporting the conjecture that temperature and salinity, but not optic conditions, are important drivers of adaptive divergence among populations. In general, these results suggest that in spite of the high degree of physical connectivity and gene flow as inferred from neutral marker genes, marine stickleback populations are strongly genetically structured in loci associated with functionally relevant genes.     

The Human Obesity Gene Map: The 2002 Update

This is the ninth update of the human obesity gene map, incorporating published results through October 2002 and continuing the previous format. Evidence from single‐gene mutation obesity cases, Mendelian disorders exhibiting obesity as a clinical feature, quantitative trait loci (QTLs) from human genome‐wide scans and various animal crossbreeding experiments, and association and linkage studies with candidate genes and other markers is reviewed. For the first time, transgenic and knockout murine models exhibiting obesity as a phenotype are incorporated (N = 38). As of October 2002, 33 Mendelian syndromes relevant to human obesity have been mapped to a genomic region, and the causal genes or strong candidates have been identified for 23 of these syndromes. QTLs reported from animal models currently number 168; there are 68 human QTLs for obesity phenotypes from genome‐wide scans. Additionally, significant linkage peaks with candidate genes have been identified in targeted studies. Seven genomic regions harbor QTLs replicated among two to five studies. Attempts to relate DNA sequence variation in specific genes to obesity phenotypes continue to grow, with 222 studies reporting positive associations with 71 candidate genes. Fifteen such candidate genes are supported by at least five positive studies. The obesity gene map shows putative loci on all chromosomes except Y. More than 300 genes, markers, and chromosomal regions have been associated or linked with human obesity phenotypes. The electronic version of the map with links to useful sites can be found at http:obesitygene.pbrc.edu .     

Fine mapping and SNP analysis of positional candidates at the preeclampsia susceptibility locus (PREG1) on chromosome 2

Genome scans in Icelandic, Australian and New Zealand, and Finnish families have localized putative susceptibility loci for preeclampsia/ eclampsia to chromosome 2. The locus mapped in the Australian and New Zealand study (designated PREG1) was thought to be the same locus as that identified in the Icelandic study. In both these studies, two distinct quantitative trait locus (QTL) regions were evident on chromosome 2. Here, we describe our fine mapping of the PREG1 locus and a genetic analysis of two positional candidate genes. Twenty-five additional microsatellite markers were genotyped within the 74-cM linkage region defined by the combined Icelandic and Australian and New Zealand genome scans. The overall position and shape of the localization evidence obtained using nonparametric multipoint analysis did not change from that seen previously in our 10-cM resolution genome scan; two peaks were displayed, one on chromosome 2p at marker D2S388 (107.46 cM) and the other on chromosome 2q at 151.5 cM at marker D2S2313. Using the robust two-point linkage analysis implemented in the Analyze program, all 25 markers gave positive LOD scores with significant evidence of linkage being seen at marker D2S2313 (151.5 cM), achieving a LOD score of 3.37 under a strict diagnostic model. Suggestive evidence of linkage was seen at marker D2S388 (107.46 cM) with a LOD score of 2.22 under the general diagnostic model. Two candidate genes beneath the peak on chromosome 2p were selected for further analysis using public single nucleotide polymorphisms (SNPs) within these genes. Maximum LOD scores were obtained for an SNP in TACR1 (LOD = 3.5) and for an SNP in TCF7L1 (LOD = 3.33), both achieving genome-wide significance. However, no evidence of association was seen with any of the markers tested. These data strongly support the presence of a susceptibility gene on chromosome 2p11-12 and substantiate the possibility of a second locus on chromosome 2q23.     

Scanning the genome for gene single nucleotide polymorphisms involved in adaptive population differentiation in white spruce

Conifers are characterized by a large genome size and a rapid decay of linkage disequilibrium, most often within gene limits. Genome scans based on noncoding markers are less likely to detect molecular adaptation linked to genes in these species. In this study, we assessed the effectiveness of a genome-wide single nucleotide polymorphism (SNP) scan focused on expressed genes in detecting local adaptation in a conifer species. Samples were collected from six natural populations of white spruce ( Picea glauca ) moderately differentiated for several quantitative characters. A total of 534 SNPs representing 345 expressed genes were analysed. Genes potentially under natural selection were identified by estimating the differentiation in SNP frequencies among populations ( F _ST) and identifying outliers, and by estimating local differentiation using a Bayesian approach. Both average expected heterozygosity and population differentiation estimates ( H _E = 0.270 and F _ST = 0.006) were comparable to those obtained with other genetic markers. Of all genes, 5.5% were identified as outliers with F _ST at the 95% confidence level, while 14% were identified as candidates for local adaptation with the Bayesian method. There was some overlap between the two gene sets. More than half of the candidate genes for local adaptation were specific to the warmest population, about 20% to the most arid population, and 15% to the coldest and most humid higher altitude population. These adaptive trends were consistent with the genes' putative functions and the divergence in quantitative traits noted among the populations. The results suggest that an approach separating the locus and population effects is useful to identify genes potentially under selection. These candidates are worth exploring in more details at the physiological and ecological levels.     

Rice TOGO Browser: A platform to retrieve integrated information on rice functional and applied genomics

The Rice TOGO Browser is an online public resource designed to facilitate integration and visualization of mapping data of bacterial artificial chromosome (BAC)/P1-derived artificial chromosome (PAC) clones, genes, restriction fragment length polymorphism (RFLP)/simple sequence repeat (SSR) markers and phenotype data represented as quantitative trait loci (QTLs) onto the genome sequence, and to provide a platform for more efficient utilization of genome information from the point of view of applied genomics as well as functional genomics. Three search options, namely keyword search, region search and trait search, generate various types of data in a user-friendly interface with three distinct viewers, a chromosome viewer, an integrated map viewer and a sequence viewer, thereby providing the opportunity to view the position of genes and/or QTLs at the chromosomal level and to retrieve any sequence information in a user-defined genome region. Furthermore, the gene list, marker list and genome sequence in a specified region delineated by RFLP/SSR markers and any sequences designed as primers can be viewed and downloaded to support forward genetics approaches. An additional feature of this database is the graphical viewer for BLAST search to reveal information not only for regions with significant sequence similarity but also for regions adjacent to those with similarity but with no hits between sequences. An easy to use and intuitive user interface can help a wide range of users in retrieving integrated mapping information including agronomically important traits on the rice genome sequence. The database can be accessed at http://agri-trait.dna.affrc.go.jp/.     

Can AFLP genome scans detect small islands of differentiation? The case of shell sculpture variation in the periwinkle Echinolittorina hawaiiensis

Genome scans have identified candidate regions of the genome undergoing selection in a wide variety of organisms, yet have rarely been applied to broadly dispersing marine organisms experiencing divergent selection pressures, where high recombination rates can reduce the extent of linkage disequilibrium (LD) and the ability to detect genomic regions under selection. The broadly dispersing periwinkle Echinolittorina hawaiiensis exhibits a heritable shell sculpture polymorphism that is correlated with environmental variation. To elucidate the genetic basis of phenotypic variation, a genome scan using over 1000 AFLP loci was conducted on smooth and sculptured snails from divergent habitats at four replicate sites. Approximately 5% of loci were identified as outliers with Dfdist, whereas no outliers were identified by BayeScan. Closer examination of the Dfdist outliers supported the conclusion that these loci were false positives. These results highlight the importance of controlling for Type I error using multiple outlier detection approaches, multitest corrections and replicate population comparisons. Assuming shell phenotypes have a genetic basis, our failure to detect outliers suggests that the life history of the target species needs to be considered when designing a genome scan.     

A genome scan to detect candidate regions influenced by local natural selection in human populations

As human populations dispersed throughout the world, they were subjected to new selective forces, which must have led to local adaptation via natural selection and hence altered patterns of genetic variation. Yet, there are very few examples known in which such local selection has clearly influenced human genetic variation. A potential approach for detecting local selection is to screen random loci across the genome; those loci that exhibit unusually large genetic distances between human populations are then potential markers of genomic regions under local selection. We investigated this approach by genotyping 332 short tandem repeat (STR) loci in Africans and Europeans and calculating the genetic differentiation for each locus. Patterns of genetic diversity at these loci were consistent with greater variation in Africa and with local selection operating on populations as they moved out of Africa. For 11 loci exhibiting the largest genetic differences, we genotyped an additional STR locus located nearby; the genetic distances for these nearby loci were significantly larger than average. These genomic regions therefore reproducibly exhibit larger genetic distances between populations than the "average" genomic region, consistent with local selection. Our results demonstrate that genome scans are a promising means of identifying candidate regions that have been subjected to local selection.     

Explorative genome scan to detect candidate loci for adaptation along a gradient of altitude in the common frog (Rana temporaria)

Today, with the rapid development of population genomics, the genetic basis of adaptation can be unraveled directly at the genome level, without any prerequisites about the selectively advantageous genes or traits. For nonmodel species, it is now possible to screen many markers randomly scattered across the genome and to distinguish between the neutral genetic background and outlier loci displaying an atypical behavior (e.g., a higher differentiation between populations). This study investigated the genetic frame of adaptation to a gradient of altitude in the common frog (Rana temporaria) by means of a genome scan based on 392 amplified fragment length polymorphism markers. Using two outlier detection methods never applied to dominant data so far, we sought for loci with a genetic differentiation diverging from neutral expectations when comparing populations from different altitudes. All the detected loci were sorted out according to their most probable cause for outlier behavior and classified as false positives, outliers due to local effects, or outliers associated with altitude. Altogether, eight good candidate loci were identified as potentially involved in adaptation to altitude because they were picked out in several independent interaltitude comparisons. This result illustrated the potential of genome-wide surveys to reveal selection signatures along selection gradients, where the association between environmental variables and fitness-related traits may be complex and/or cryptic. In this article, we also underlined the need for confirmation of the selection footprints for the outlier loci. Finally, we provided some preliminary insights into the genetic basis of adaptation along an altitudinal cline in the common frog.     

The Human Obesity Gene Map: The 2004 Update

This paper presents the eleventh update of the human obesity gene map, which incorporates published results up to the end of October 2004. Evidence from single‐gene mutation obesity cases, Mendelian disorders exhibiting obesity as a clinical feature, transgenic and knockout murine models relevant to obesity, quantitative trait loci (QTLs) from animal cross‐breeding experiments, association studies with candidate genes, and linkages from genome scans is reviewed. As of October 2004, 173 human obesity cases due to single‐gene mutations in 10 different genes have been reported, and 49 loci related to Mendelian syndromes relevant to human obesity have been mapped to a genomic region, and causal genes or strong candidates have been identified for most of these syndromes. There are 166 genes which, when mutated or expressed as transgenes in the mouse, result in phenotypes that affect body weight and adiposity. The number of QTLs reported from animal models currently reaches 221. The number of human obesity QTLs derived from genome scans continues to grow, and we have now 204 QTLs for obesity‐related phenotypes from 50 genome‐wide scans. A total of 38 genomic regions harbor QTLs replicated among two to four studies. The number of studies reporting associations between DNA sequence variation in specific genes and obesity phenotypes has also increased considerably with 358 findings of positive associations with 113 candidate genes. Among them, 18 genes are supported by at least five positive studies. The obesity gene map shows putative loci on all chromosomes except Y. Overall, >600 genes, markers, and chromosomal regions have been associated or linked with human obesity phenotypes. The electronic version of the map with links to useful publications and genomic and other relevant sites can be found at http:obesitygene.pbrc.edu .     

Adaptation of redband trout in desert and montane environments

Natural populations that evolve under extreme climates are likely to diverge because of selection in local environments. To explore whether local adaptation has occurred in redband trout (Oncorhynchus mykiss gairdneri) occupying differing climate regimes, we used a limited genome scan approach to test for candidate markers under selection in populations occurring in desert and montane streams. An environmental approach to identifying outlier loci, spatial analysis method and linear regression of minor allele frequency with environmental variables revealed six candidate markers (P < 0.01). Putatively neutral markers identified high genetic differentiation among desert populations relative to montane sites, likely due to intermittent flows in desert streams. Additionally, populations exhibited a highly significant pattern of isolation by temperature (P< 0.0001) and those adapted to the same environment had similar allele frequencies across candidate markers, indicating selection for differing climates. These results imply that many genes are involved in the adaptation of redband trout to differing environments, and selection acts to reinforce localization. The potential to predict genetic adaptability of individuals and populations to changing environmental conditions may have profound implications for species that face extensive anthropogenic disturbances.     

The Human Obesity Gene Map: The 2000 Update

This report constitutes the seventh update of the human obesity gene map incorporating published results up to the end of October 2000. Evidence from the rodent and human obesity cases caused by single‐gene mutations, Mendelian disorders exhibiting obesity as a clinical feature, quantitative trait loci uncovered in human genome‐wide scans and in cross‐breeding experiments in various animal models, and association and linkage studies with candidate genes and other markers are reviewed. Forty‐seven human cases of obesity caused by single‐gene mutations in six different genes have been reported in the literature to date. Twenty‐four Mendelian disorders exhibiting obesity as one of their clinical manifestations have now been mapped. The number of different quantitative trait loci reported from animal models currently reaches 115. Attempts to relate DNA sequence variation in specific genes to obesity phenotypes continue to grow, with 130 studies reporting positive associations with 48 candidate genes. Finally, 59 loci have been linked to obesity indicators in genomic scans and other linkage study designs. The obesity gene map reveals that putative loci affecting obesity‐related phenotypes can be found on all chromosomes except chromosome Y. A total of 54 new loci have been added to the map in the past 12 months and the number of genes, markers, and chromosomal regions that have been associated or linked with human obesity phenotypes is now above 250. Likewise, the number of negative studies, which are only partially reviewed here, is also on the rise.