The National Research Council recommends that genetic differentiation among subgroups of ethnic samples be lower than 3% of the total genetic differentiation within the ethnic sample to be used for estimating reliable random match probabilities for forensic use. Native American samples in the United States’ Combined DNA Index System (CODIS) database represent four language families: Algonquian, Na-Dene, Eskimo-Aleut, and Salishan. However, a minimum of 27 Native American language families exists in the US, not including language isolates. Our goal was to ascertain whether genetic differences are correlated with language groupings and, if so, whether additional language families would provide a more accurate representation of current genetic diversity among tribal populations. The 21 short tandem repeat (STR) loci included in the Globalfiler® PCR Amplification Kit were used to characterize six indigenous language families, including three of the four represented in the CODIS database , and two language isolates (Miwok and Seri) using major population genetic diversity metrics such as F statistics and Bayesian clustering analysis of genotype frequencies. Most of the genetic variation (97%) was found to be within language families instead of among them (3%). In contrast, when only the three of the four language families represented in both the CODIS database and the present study were considered, 4% of the genetic variation occurred among the language groups. Bayesian clustering resulted in a maximum posterior probability indicating three genetically distinct groups among the eight language families and isolates: (1) Eskimo, (2) Seri, and (3) all other language groups and isolates, thus confirming genetic subdivision among subgroups of the CODIS Native American database. This genetic structure indicates the need for an increased number of Native American populations based on language affiliation in the CODIS database as well as more robust sample sets for those language families.Supplemental data for this article is available online at https://doi.org/10.1080/20961790.2021.1963088 . The Combined DNA Index System (CODIS) refers to the Federal Bureau of Investigation’s (FBI) software associated with forensic DNA databases maintained at the local, state, and federal levels. CODIS has three primary databases: the offender/arrestee, missing persons, and forensic casework databases. The offender reference database consists of profiles belonging to convicted individuals and arrestees depending on local and federal laws. When dealing with an offender profile, there are two primary ways in which identification is made: 1) the profile of an unknown offender is searched against the CODIS offender/arrestee database to either identify a suspect from known offenders or make connections between crimes and (2) generating a random match probability, the probability that a random individual from a given population exhibits the particular combination of alleles exhibited by a known, suspected individual. Because some alleles and allele combinations have a higher frequency in some populations than in others, separate databases for the different ethnic populations found in the US are required to account for population-specific allele frequencies when estimating random match probabilities [ the profwww.ethnologue.com, accessed 13 May 2018). As a language changes over time, its divergence can be characterized much the same way as gene divergence is illustrated using a phylogenetic tree [Language affiliation has often been used to define membership in genetically distinct populations. While as many as 7 097 distinct languages are currently spoken worldwide, only 23 are spoken by more than half the world’s populations  and two language isolates were analyzed using the 21 autosomal loci included in the Globalfiler• PCR Amplification kit to characterize their genetic structure, composition and differentiation. That level of differentiation, represented by via the spread of farming practices, but not necessarily genes, from Mexico into the American Southwest [Mitochondrial DNA (mtDNA) and Y chromosome-linked short tandem repeat (Y-STR) evidence reveals a greater genetic diversification among  Native American populations speaking different languages than among populations speaking different languages in other parts of the world . There aouthwest . This isouthwest . Howeverouthwest .via the Beringian Strait beginning approximately 20–25 kya [Native American populations have become further subdivided linguistically due to physical isolation  as they 0–25 kya . The iso0–25 kya  resulted0–25 kya   to evaluate nuclear genetic diversity, differentiation, and structure within and among samples of six Native American language families and two language isolates that represent a wide geographic range covering the Arctic, the Midwestern, Southwestern, and Southeastern US, California/Great Basin and Mexico, including Baja California , as prevn ≥ 25 samples per language family or isolate; Five hundred and two samples representing members of six language families and two language isolates  with POP-4 polymer (Applied Biosystems) according to run conditions and protocols recommended by the manufacturer. Profiles were analyzed using GeneMapper• ID-X v 1.4 (Applied Biosystems) and the Local Southern sizing method. Samples with saturated off-scale alleles were diluted based on the severity of the pull-up and re-injected.The concentrations of the 502 extracted DNA samples, as well as the Standard Reference Material (SRM) 2391c reference DNA , were normalized to approximately 1.0 ng/µL and amplified using the Globalfiler• PCR Amplification Kit following manufacturer protocols. The Globalfiler• Kit consists of the following autosomal STR loci that were selected to maximize discrimination potential for human identification and kinship analyses : CSF1PO,A), observed heterozygosity (HO), and expected heterozygosity (HE) were estimated using ARLEQUIN v3.5.1.2 [R) were calculated across all 21 loci for each language group and isolate after their sample sizes were normalized to the smallest population size using the Allelic Diversity Analyzer (ADZE) software programme [F-statistics FIS  and FIT  inbreeding coefficients, and FST, the proportion of genetic variance in a population that is due to differences among subdivisions within that language sample; pairwise FST, the degree of differentiation between pairs of language samples, was also calculated to provide insight into the historical connections among these languages [FST computations was determined with a probability distribution constructed from permutation tests (N = 1 000) with Bonferroni corrections for multiple comparisons. The P-values for deviations from Hardy-Weinberg Equilibrium (HWE) for each locus in each language group were estimated with GENEPOP 4.2 [The allele frequency distribution, average number of alleles , each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample were assigned probabilistically to a specific genetic group or jointly to two or more genetic groups if their genotypes indicate they are admixed. Each run used 500 000 estimation iterations for K = 1 to 8 after a 100 000 burn-in length. Each run was carried out five times for each value of K. The log probability of the data (Ln P(D)) and delta K  and lowest standard deviation) were used to determine the true number of genetically distinct populations [An analysis of molecular variance, AMOVA , was perulations  represenA estimates for the eight language families or isolates ranged from 5.52 (Eskimo) to 9.43 (Uto-Aztecan). No deviation in NA estimates attributable to variation in sample sizes of language groups was detected (n = 130) and Algonquian (n = 25) language families had the largest and smallest sample sizes, respectively, but the NA estimates from both these groups were comparable, i.e. 7.62 and 7.95, respectively. Moreover, the highest NA estimate represented the Uto-Aztecan language family (9.43), only the second largest language sample in this study (n = 112), and the smallest NA estimate represented the Eskimo-Aleut language family (5.52), whose sample size (n = 44) was almost twice that for the Algonquian language family (n = 25) which represented the smallest sample size. All language groups and isolates included in this study contained NR values between 4.68 (Na-Dene) and 6.61 (Algonquian), reflecting a minimal impact of sample size (n = 29) to 0.78 (Algonquian n = 25 and Miwok n = 33) and EH values ranging from 0.64 (Seri n = 29) to 0.77 (Algonquian n = 25 and Iroquoian n = 33). All language groups exhibited either no marker or only a single marker violating HWE at the 0.01 level of probability with the exception of the Yuman, which had four loci not in HWE (P = 0.01 level of probability (Supplementary Table S9).Ndetected . For insple size . The valt in HWE . None ofbability , and wheFST estimates and average FIS are presented in FST values ranged from 0.011 (between the Na-Dene and Yuman speakers) to 0.113 (between the Eskimo-Aleut and Seri speakers), and all were statistically significant at the 0.05 level of probability. Both the Eskimo-Aleut language family and the Seri language isolate exhibited the greatest average genetic divergence from the other populations with mean pairwise FST values of 0.069 and 0.072, respectively, while the Yuman language family had the lowest population-specific FST (0.028). FIS values  indicating genetic subdivision among the eight language families or isolates (K = 3), the STRUCTURE analysis reflected a strong correlation between genotypic distributions and membership in each of the three groups  and delta isolates . Assumine groups . While me groups  being pre groups . Only fie groups . Three ae groups . While tAL*Naskapi [FST and FIS values  provide evidence to support that the loss of heterozygosity levels, which contributed to each group’s violation of HWE is caused by non-random mating, genetic subdivision, and genetic drift among the language samples. The use of these estimates to ascertain genetic structure and gene flow overcomes sampling issues because it considers resampling over replicate populations [FST performs well in cases with moderate amounts of gene flow and large population sizes as it does not tend to overestimate genetic subdivision [The ulations , 36. Thidivision , 45.FST values indicate varying allele frequencies within language families/isolates and average allele frequencies across all language samples included in this study. The low-to-moderate pairwise FST values suggest that not all language families and isolates examined are differentiated, likely resulting from increased gene flow or recent common ancestry. Pairs of language groups that are geographic neighbors tend to be more genetically similar than groups that are more geographically distant, regardless of whether the languages are closely related [FST comparisons show that the Eskimo-Aleut and Seri language samples, which, incidentally, are fixed for mtDNA haplogroups A and C, respectively – comprise the most genetically distinct individuals in the study, likely due to their extant geographic isolation from the other samples. It has previously been shown that the Seri population experienced a genetic bottleneck due to reduced gene flow via historical isolation and is distinct from populations in the Uto-Aztecan language group [Language group-specific  related . In conjge group  that livFIT of 0.051 points to a general deviation from HWE frequencies due to an excess of homozygotes even when all samples are combined. As FIS estimates indicate any deviation of the average allele frequency from HWE is probably due to consanguineous mating, the positive FIS values for Na-Dene, Eskimo-Aleut, Iroquoian, Uto-Aztecan, and Yuman speaking groups may reflect an increased relatedness among individuals who speak those languages rather than geographic isolation. In contrast, while inbreeding and geographic isolation are related phenomena, the Miwok and Seri language samples exhibit negative FIS values due to the absence of significant inbreeding despite being isolated linguistically or geographically. This finding suggests that these isolated language groups are more susceptible to genetic distinction due to loss of genetic variation from isolation and drift and not due to consanguineous mating.Ignoring group structure, an overall FST analyses (0.032) was very similar to earlier values reported (FST=0.03) [Interestingly, while the overall level of genetic diversification among the language samples in this study revealed by the ST=0.03) , based oST=0.03)  based onST=0.03) . This isST=0.03) .The geographic distribution of Native Americans has changed dramatically over the past five centuries owing to unique historical events such as early Spanish colonization, European immigration, and forced resettlement . MigratiThe Apache and Navajo tribes in the CODIS database are southwestern US speakers of the Athabaskan languages of the Na-Dene language family , 52 and FST value for the three language families shared between our dataset and the CODIS database  are combined, their FST value is 0.04, 33% higher than the 0.03 FST value recommended by the National Research Council for random match probability generation [FST=0.032, a value much closer to the recommended value, indicating the necessity to increase the number of language families included in the Native American CODIS database. The addition of a still greater number of language families to the CODIS database could undoubtedly provide a Native American database more representative of all Native Americans in the US and whose FST value is lower than the recommended value of 0.03. The use of frequency databases comprising additional language groups spoken by Native American profile contributors would provide more accurate random match probabilities, even if it does not account for the more rapid and complicated spread of languages than genes in North America between geographically disparate populations [When the neration . When thulations . The COD


Polyarthra dolichoptera and P. vulgaris are cosmopolitan rotifers that are tolerant to environmental changes, offering an excellent model to address the research gap. Here, we investigated the populations in Southeastern China and eastern North America and evaluated the phylogeographical patterns from their geographical range sizes, geographic–genetic distance relationships and their responses to spatial‐environmental factors. Using the mitochondrial cytochrome c oxidase subunit I gene as the DNA marker, we analyzed a total of 170 individuals. Our results showed that some putative cryptic species, also known as entities were widely distributed, but most of them were limited to single areas. The divergence of P. dolichoptera and P. vulgaris indicated that gene flow between continents was limited while that within each continent was stronger. Oceanographic barriers do affect the phylogeographic pattern of rotifers in continental waters and serve to maintain genetic diversity in nature. The genetic distance of P. dolichoptera and P. vulgaris populations showed significant positive correlation with geographic distance. This might be due to the combined effects of habitat heterogeneity, long‐distance colonization, and oceanographic barriers. Furthermore, at the intercontinental scale, spatial distance had a stronger influence than environmental variables on the genetic differentiations of both populations. Wind‐ and animal‐mediated transport and even historical events of continental plate tectonics are potential factors for phylogeography of cosmopolitan rotifers.Genetic differentiations and phylogeographical patterns of small organisms may be shaped by spatial isolation, environmental gradients, and gene flow. However, knowledge about genetic differentiation of rotifers at the intercontinental scale is still limited.  Oceanographic barriers affect the phylogeographic pattern of rotifers in continental waters and maintaining genetic diversity in nature. The divergence indicates that gene flow between eastern North America and Southeastern China is limited while that within eastern North America or Southeastern China was higher. Spatial variables are key factors in affecting the genetic differentiation of rotifers when compared with environmental variables on the intercontinental scale. Water temperature (Temp) was measured on site. Total dissolved phosphorus (TP) and total dissolved nitrogen (TN) were determined in the laboratory following standard analytical methods  horizontally at surface and subsurface depths and preserved in 50‐ml centrifuge tubes. Samples were fixed on site immediately with neutral Lugol's solution at 2% final concentration and transported in a cooler before storing at −20°C. In vivo semi‐quantitative measurements of chlorophyll‐2.2P. dolichoptera and P. vulgaris are similar in morphology, they can still be distinguished by morphological features such as body sizes and fins. For P. dolichoptera, the main fins are as long or longer than body length; width/length 1:10–1:15, serration coarse, widely spaced, uniformly sword‐like with central rib almost reaching the end; serration lines faint or absent. For P. vulgaris, the main fins are as long or shorter than body length but broader than that of P. dolichoptera; width/length 1:5–1:7, feathery or leaf‐like with strong central rib. Each identified individual was isolated with micropipette under the stereomicroscope (Olympus SZX16)  Figure . Single 2.3DNA from each single animal was extracted following the HotSHOT protocol  were calculated using DNASP 5.1 . The selected model of evolution for phylogenetic reconstructions was HKY + I + G, chosen by approximate likelihood ratio tests in ModelGenerator v0.85   was included as outgroup, and P. dolichoptera (KC618934) was included as outgroup for P. vulgaris.Bayesian phylogenetic trees were run in BEAST v1.8.4 . ABGD classifies sequences into putative entities based on pairwise genetic distances without any prior assumptions  was applied to ultrametric BEAST trees using the default settings to detect the number of entities , and coalescence (within species events)  in genetic distances among three different groups, analysis of variance (ANOVA) with TukeyHSD test was conducted, using the software R 3.6.1, “agricolae,” “car,” and “multcomp” packages.The geographic distance matrices were calculated in R 3.6.1 , environmental and spatial factors using the “vegan” and “ggplot2” packages in R. If the longest gradient is >4, the unimodal method (CCA) can be applied. On the other hand, if that value is <3, the linear method (RDA) is a better choice. In the range between 3 and 4, both methods can be applied  variables  should be carried out. CCA or RDA model is determined based on the 27 sample datasets Table  by detre33.1P. dolichoptera and 63 sequences of P. vulgaris, with aligned lengths of 562p and 589 bp, respectively (Accession numbers: Table P. dolichoptera haplotypes were detected with haplotype diversity (h) of 0.98 and nucleotide diversity (π) of 0.175. For P. vulgaris, a total of 36 haplotypes were found with a haplotype diversity of 0.96 and nucleotide diversity of 0.106 , nucleotide diversity , average number of nucleotide differences , and average number of segregating sites . For P. vulgaris population, higher levels of dH (0.93), π (0.048), K (27.56), and S (156) were detected in the Southeastern China samples .A large number of cryptic entities were detected using three independent methods Figures  and 4. T3.3P. dolichoptera and P. vulgaris species were widely distributed, with the geographic range sizes up to 12,903 and 12,836 km, respectively. Their range sizes at cryptic entities and haplotype levels decreased to 2726 and 411 km, respectively. These correspond to the mean range sizes at species level  significantly larger than at entities (463 ± 815 km) and haplotype level (12 ± 61 km) (p < .05). However, there was no significant difference in range size between entities and haplotype ranges.The range size of geographic distances declined as the resolution of classification increased from morphological species to cryptic entities to haplotype Figure . Both P.P. vulgaris population (V1) comprised individuals from as distant areas as Changde (liuye), Wuhan (WHS7), Xiamen (XM), and Guangzhou (zhujiangpark), in China  was as widely distributed as from Connecticut (P4), Long Island (SUC), and Niagara (upstate New York), in United States. In contrast, some entities only occurred in one sampling site, such as D7 and D16    Figure . The gen) Figure .P. dolichoptera and P. vulgaris populations, the mean genetic distances between the two continents were significantly higher than those within either eastern North America or Southeastern China (p < .05)  > within eastern North America (0.188 ± 0.111) > within Southeastern China (0.173 ± 0.089)  > within Southeastern China (0.055 ± 0.088) > within eastern North America (0.049 ± 0.067) . This suggests that there is a higher level of gene flow and higher frequency of recombination within continents than between continents.Our results indicated that in both ) Figure . The mea) Figure . The mea) Figure . However3.5P. dolichoptera and P. vulgaris), spatial and environmental factors. The first two ordinate axes explained 49.5% of the entities distribution, spatial and environment variability in the CCA ordination (Table p < .05)  tended to be restricted to specific regions.As the longest gradient performed by detrended correspondence analysis (DCA) was 7.5  Table . Howeverns Table . Figure 44.1P. dolichoptera and P. vulgaris.Nuclear  ribosomal RNA genes, nuclear internal transcribed spacer (ITS), and mitochondrial cytochrome c oxidase subunit I gene (COI) are widely used as DNA barcodes for identification   at different sites and we found that the haplotypes belonged to different clades. Therefore, food sources level might not be an influencing factor for their genetic divergence. Dispersal, genetic diversity and gene flow can be strongly affected by temperature changes  ; Investigation (lead); Methodology ; Resources (lead); Software (lead); Writing – original draft (lead). George McManus: Writing – review & editing . Qing Wang: Writing – review & editing . Xian Sun: Writing – review & editing . Zhiwei Liiu: Software . Senjie Lin: Supervision ; Writing – review & editing (lead). Yufeng Yang: Project administration (lead); Supervision (lead).Supplementary MaterialClick here for additional data file.


The settlement of the Americas has been the focus of incessant debate for more than 100 years, and open questions regarding the timing and spatial patterns of colonization still remain today. Phylogenetic studies with complete human Y chromosome sequences are used as a highly informative tool to investigate the history of human populations in a given time frame. To study the phylogenetic relationships of Native American lineages and infer the settlement history of the Americas, we analyzed Y chromosome Q Haplogroup, which is a Pan-American haplogroup and represents practically all Native American lineages in Mesoamerica and South America. We built a phylogenetic tree for Q Haplogroup based on 102 whole Y chromosome sequences, of which 13 new Argentine sequences were provided by our group. Moreover, 1,072 new single nucleotide polymorphisms (SNPs) that contribute to its resolution and diversity were identified. Q-M848 is known to be the most frequent autochthonous sub-haplogroup of the Americas. The present is the first genomic study of Q Haplogroup in which current knowledge on Q-M848 sub-lineages is contrasted with the historical, archaeological and linguistic data available. The divergence times, spatial structure and the SNPs found here as novel for Q-Z780, a less frequent sub-haplogroup autochthonous of the Americas, provide genetic support for a South American settlement before 18,000 years ago. We analyzed how environmental events that occurred during the Younger Dryas period may have affected Native American lineages, and found that this event may have caused a substantial loss of lineages. This could explain the current low frequency of Q-Z780 . These environmental events could have acted as a driving force for expansion and diversification of the Q-M848 sub-lineages, which show a spatial structure that developed during the Younger Dryas period. The human settlement of the American continent has been subject of extensive debate and controversy in the academic community for more than 100 years ; centralde novo phylogenetic trees based on a large set of mutational data, where the branch lengths are proportional to the number of SNPs and, therefore, to time . G–7. G5–7]The Q-MPB118 sub-lineage was found here defining the same Aranã samples from Southeast Brazil and Xavante from West Brazil , in agreQ-MPB118 supports a lineage ancestry shared between native Xavante and Aranã groups, both of the Macro-Jê linguistic trunk. Since its differentiation (~9.7 kya), this lineage is present among human groups from Central-West and Southeast Brazil, although further study on its distribution is still necessary. For a schematic representation of the geographic distribution of Q-MPB118, see Q-SK281 is currently presented as a restricted lineage for Peruvian individuals , dated 1Uro samples from Peru and Pasto from Ecuador were found here supported by Q-MPB139 in agreement with previous reports . The datQ-MPB139 shows a shared lineage ancestry between the Uros of Peruvian Altiplano and the Pasto of the Ecuadorian Altiplano, evidencing a great temporal depth and vast movements of human groups between the Central and North Andean Areas, near 14 kya (12.4–15.9). For a schematic representation of the geographic distribution of Q-MPB139, see Q-B46 has been previously described as characteristic of Colla individuals from Salta , 52, whiAlthough this lineage still has very few sequences and its dating has not been established, its phylogenetic relationship is expected to be found since the autochthonous peoples of the Northwestern region of Argentina have remained permanently related to each other since ancient times, through exchange, trade, migration, and the promotion of their artistic and craftwork materials .So far, the Q-B43 sub-lineage has been described by other authors in Wichi individuals from Salta, Argentina , and in The phylogenetic relationship found in this work for 3 individuals from East Salta, Argentina, was supported by Q-Z35505, parallel to Q-B43 . MoreoveThe dating of this lineage had been previously estimated as 1.5 kya (0.9–2.1) , calculaIn this study we present genetic evidence that associates within the same sub-lineage (Q-Z35505/Q-Z35497) Mataguayan-speaking individuals from Gran Chaco and Arawak-speaking individuals from the Mato Grosso region, bordering the Gran Chaco  and Q-B46 . Q-B42 iQ-B42 occurs among individuals from Peru, Northwest Argentina, and Central Chaco. For the Huaca Prieta archaeological site located near the Pacific coast in Northern Peru, radiocarbon dating indicates intermittent human presence between ~15,000 and 8,000 cal BP . In NortAs proof of the influence of the first civilizations of the Andean highlands on Northwestern Argentina, such as the pre-Inca culture of Tiwanaku located near Titicaca Lake within the current territory of Bolivia, cultural legacy has been found in Peru, Chile, and elsewhere Northwestern Argentina . The ColThe Q-CTS2731 lineage is currently restricted to native populations of the United States and Mexico , 75. We Q-Y26467 has been described as characteristic of the Zapotec male population of Mexico , which hThe timing found for the first human occupation in Mexico is currently under discussion. Archaeological studies consider that Mexico shows consistent evidence of human occupation from at least 40–30 kya , 77–81, It is known that the writing style used in the Central Valleys of Oaxaca, belonging to the Zapotec scribal tradition, constitutes the earliest evidence of writing in the American continent. The first tangible manifestations of the graphic system can be dated to approximately 600 years before the Common Era . These aThis lineage is known to have a wide distribution beginning at Southwest United States and extending through Mexico, Central America, and South America , 52, 83.Q-CTS11357 is classified into the following sub-lineages:Q-Z5917 found in individuals from Colombia in the present study and in individuals from Panama and Nicaragua from the databases , 84.Q-SK1974   is curreQ-BZ4012 is at the moment restricted to individuals from the United States , is abseQ-CTS11330 has been described in this and other research works as characteristic of Mexican individuals , 6 thougThe Q-CTS11357 lineage is represented by individuals of the Pima and Nahua, speakers of the Uto-Aztecan language, and Karitiana ethnic groups, speakers of the only remnant of the Arikém linguistic family, being a sub-family of the Tupí linguistic trunk see . For a sCurrently, this lineage has been reported for individuals from Mexico and Argentina , 89. TheThe time estimate found for this lineage is 16.1 kya (14.2–18.2) see , older tQ-Y27993 occurs among individuals from Mexico and Chané from Northern Argentina. The language spoken by the Chané belongs to the Arawak linguistic group, one of the largest and most dispersed linguistic families in the Americas . Q-Y2799This lineage has been reported before in Peru  and in AQ-Z19357 provides evidence of a shared lineage ancestry among individuals from Andean Peru, Northwestern Argentina, and the Brazilian Maxakalí ethnic group with a temporal depth of 8.1 kya 9.5–6.7), as reported in the literature . ThIncreasing archaeological evidence proves the early human presence in the American continent. Recent archaeological excavations in the Chiquihuite cave in Northern Mexico demonstrate human occupation dating from ~26,500 years ago , and theThe current Native American male sub-lineages discussed before in this study are analyzed here according to their temporal depth and are contrasted with updated archaeological information which allows to infer the history of the American settlement. In Although currently there is practically one single individual from each sub-lineage and geographic area, in the Hypothesis of the American Settlement of this paper, we assume that each individual is representative of the present and past populations of an area in light these are the only data available to date. We acknowledge that a higher number of representatives of these sub-lineages in each area would be very valuable to estimate the frequency and to be able to draw more complete historical inferences, but the extremely low frequency of Q-Z780 makes those representatives quite difficult to be found.We estimated a temporal depth of 19.3 kya (17–21.9) for Q-Z780 and Q-Z781. This temporal depth and the presence of these lineages in Mexico and Brazil are consistent with the dates estimated for the human presence from the archaeological sites mentioned in Mexico  and in NThe Younger Dryas (YD) event, spanning 12,900–11,600 cal BP period, was known as a rapid cooling in the Northern hemisphere , 101. GrThe YD impact hypothesis states that fragments of a large disintegrating asteroid/comet hit North America, South America, Europe, and Western Asia at 12,800 cal BP , 24, 108The study of how the YD event affected human populations of the time has been considered by archaeologists worldwide . A studyUnfortunately, there are few archaeological studies that focus on how the YD event affected human populations in Mesoamerica and South America –119. A rin vivo and in vitro [Currently, analyses of the effects caused at the level of the human genome by the environmental changes produced during the YD period are rather scarce. There is increasing evidence of large-scale biomass burning during the YD recorded in Europe, Asia, and North America, and even South America, where the archaeological record is consistent with regional forest fire activity, which indicates that anomalous biomass burning reached high latitudes in the Southern hemisphere , 112. Thin vitro , 124.In this work it is proposed that the population foci that existed ~19.3 kya in what is now Mexico, Peru, Argentina, and Brazil could have been drastically affected by the environmental episode that occurred during the YD period. The Q-Z780 lineage, and perhaps Q-F4674, could have comprised a much larger population before the YD, and suffered after this event a substantial decrease that could not be reverted to the number it showed previously to the YD. Therefore, we propose that the environmental events occurred during the YD could represent one of the fundamental reasons for the current low frequency of the Q-Z780 and Q-F4674 lineages in the Americas.The most prevalent Native American lineage currently Q-M848, with a temporal depth of ~15.4 kya, coexisted before the YD event along with Q-Z780, but seems to have been more successful in surviving to the environmental changes that occurred during the YD period. If we consider the divergence times average, only 3 Q-M848 sub-lineages are older than 12.9 kya see , and allMost of the genetic records of current male Native American sub-lineages are those derived from Q-M848 after 12,900 cal BP, so, much of the current genetic diversity present in male Native American lineages could be represented by those sub-lineages that achieved to survive, expand and diversify after the environmental events of the YD period. This could suggest an extinction and loss in the gene pool of a large part of the sub-lineages existing previously to the environmental events during this period.In this regard, a recent archaeological study compiles the data set of 1,661 radiocarbon early dates  from 454 archaeological sites in South America  [Prates et al.  also sugConsidering an abrupt population decline in Native American populations as a result of the environmental adversities during the YD period makes it more difficult to understand the demographic processes that underlie the current distribution of the Q-M242 haplogroup in Euro-Asia and its links with the Native American lineages. We propose that if the Middle East did not have a population decline during the YD period but rather served as a refuge for humans of the time , 116, thAnother important aspect for the study of the history of the American settlement is that global sea levels rose sharply and rapidly by ~120 m by the time of the YD . In SoutQ-Z780 and Q-Z781 sub-lineages, autochthonous of the Americas, presented a wide distribution in Mesoamerica and South America since ~19,300 years ago. This contributed to a regional differentiation from Q-Y2816 and Q-Z782 for individuals from Mexico, Q-YP937 among individuals from Peru, Brazil, and Argentina since ~18,700 years, and Q-GMP73 among individuals from the Central Andes and Central West of Argentina since ~18,200 years ago. Moreover, it provided genetic support for South American settlement before 18,000 years ago, in agreement with a long chronology scenario and the dates of Meso- and South American archaeological sites , 98, 99.The Q-Z780 lineage, and perhaps Q-F4674, could have suffered a substantial drop due to the environmental events occurred during the YD, which could be the main reason for its current low frequency. For the Q-M848 lineage the YD environmental events could have acted as a driving force for its expansion and diversification, and while they could have also caused a substantial decrease, this lineage survived more successfully than Q-Z780. The upper and lower limits of all divergence times for Q-M848 sub-lineages cover the YD period or later. The spatial structure of the South American male population at ~12.3 kya , and theUnderstanding the relationship between the Eurasian and American Q-M242 lineages becomes more complex when population changes during the YD period are included , 115. SiThe reconstruction of the first South American settlements still requires further studies. Y chromosome NGS sequencing has proven to be a highly important tool, and future studies with a larger number of diverse individuals with Native American ancestry from all over the continent, as well as a larger number of sequences belonging to ancient Native American sub-lineages, would highly contribute to this field. Furthermore, in order to gain insight into our ancient history, additional multidisciplinary efforts should focus on studying what caused the environmental changes that occurred during the YD period and what the spatial structure of the environment and human populations were like before this event.Argentine samples were collected from volunteers from San Juan (San Juan), Malargüe (Mendoza), Lavalle (Mendoza), La Quiaca (Jujuy), Santa María (Catamarca), Belén (Catamarca), Tartagal , Bariloche (Rio Negro), and El Chalía (Chubut) during campaigns carried out at different times. Samples were evaluated by two different Ethics Committees: Provincial Bioethics Committee of the Province of Jujuy and Instituto Multidisciplinario de Biología Celular (IMBICE) Ethics Committee . All bioThe DNA from the 13 samples was sent to Full Genomes Corporation  for sequPaired-end reads obtained from sequencing of whole Y genomes samples were analyzed using FastQC  and trimWe reviewed public databases for more samples belonging to the Q-M242 haplogroup see . Some weWe built a phylogenetic tree from 102 sequences belonging to Q-M242 haplogroup plus a sequence from B2b1 haplogroup  used as a phylogenetic root. A multiple sequence alignment (MSA) was performed using the "phylo fasta" option of the VCF-kit software , 145, thFor the construction of the maximum likelihood phylogenetic tree, the parameters of Pinotti et al.  were fol-9 mutations per site per year was used, with a 95% confidence interval of 0.67x10-9 to 0.86x10-9.For the dating of the phylogenetic nodes, the calculation of ρ (rho) statistics  was usedSince dating calculations are affected by the amount of information from the sequences, in this study for the dating estimates we used only those samples that are available as complete sequences Click here for additional data file.S1 FigColored circles represent the geographic distribution and sub-lineage membership, as shown in the inset tree. The size of the circles is related to the number of subjects and is specified with the "n" in the box to the right, see (PNG)Click here for additional data file.S2 FigColored circles represent the geographic distribution and sub-lineage membership, as shown in the inset tree. The size of the circles is related to the number of subjects and is specified with the "n" in the box to the right, see (PNG)Click here for additional data file.S3 FigColored circles represent the geographic distribution and sub-lineage membership, as shown in the inset tree. The size of the circles is related to the number of subjects and is specified with the "n" in the box to the right, see (PNG)Click here for additional data file.S4 FigColored circles represent the geographic distribution and sub-lineage membership, as shown in the inset tree. The size of the circles is related to the number of subjects and is specified with the "n" in the box to the right, see (PNG)Click here for additional data file.S5 FigThe colors of each individual of the tree are according to the macro-area or the country according to the box on the left. The dashed lines are used to represent branches that require to be further studied for a better definition. The length of the branches is represented as a function of time in kya according to the axis represented. The nodes without asterisks are those dated in this study. The red asterisks are the nodes that could not be dated and the length of their branches does not represent a defined time depth. The green asterisks represent the dates taken from the literature; for a complete list of the dates used in this figure, see (PDF)Click here for additional data file.S6 FigThe length of the branches is expressed as a function of the number of SNPs found in each one. The asterisk indicates samples available only as VCF (see Section 3 in (PDF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.


Morinda officinalis How (MO) is a perennial herb distributed in tropical and subtropical regions, which known as one of the “Four Southern Herbal Medicines”. The extent of genetic variability and the population structure of MO are presently little understood. Here, nine morphological traits, six chemical components and Single nucleotide polymorphism (SNP) markers were used in integrative research of MO germplasm variation among 88 individuals collected from ten populations across four geographical provinces of China.F-furanosaccharide nystose, and the section color were the major contributors to diversity. The cluster analysis based on phenotypic and oligosaccharide data distinguished three significant groups, which was consistent with the result of a corresponding analysis with 228,615 SNP markers, and importantly, they all showed a significant correlation with geographical origin. However, there was little similarity between two cluster results. The Shannon’s information index (I) varied from 0.17 to 0.53 with a mean of 0.37, suggesting a high level of genetic diversity in MO populations, which mainly existed among individuals within populations, accounting for 99.66% of the total according to the analysis of molecular variance (AMOVA) results. Each population also maintains the connection because of certain gene communication, so that the genetic differentiation between populations was not very significant. The STRUCTURE software was used to analyse the population structure and the result showed that 88 accessions were clustered into three groups, and 67% of them were pure type, which was also confirmed through PCA.Both phenotype and chemical composition have significant genetic variation, and there is a certain correlation between them such as root diameter and the nystose content, as well as geographical distribution. The principal component analysis (PCA) showed the leaf length, leaf width, nystose, 1The comprehensive study of phenotypic, chemical and molecular markers will provide valuable information for future breeding plans and understanding the phylogenetic relationship of MO population.The online version contains supplementary material available at 10.1186/s12864-022-08817-w. Morinda officinalis How (MO) is a monoecious, perennial vine, widely distributed in tropical and subtropical regions. It is native to the mountainous regions of southern in China such as Guangdong and Fujian provinces [rovinces  and as orovinces –5, and arovinces , 7. Moderovinces –12. The rovinces .Fusarium wilt and causes serious degradation of the species. The diversity of germplasm provides plant breeders with the opportunity to develop new varieties and improved them with excellent traits, and is also the basis for limiting genetic erosion. Previous studies have shown that there were significant differences in the appearance traits of different germplasm resources of MO, as well as the chemical components, for example, the leaves of MO from Guangdong province were leathery, with protrusions, pubescent at both upper and lower surface, with high content of nystose, while leaves from Hainan were obviously hairy, more smooth and with extremely low nystose [The collection and research of germplasm resources is a vital pillar to initiate breeding programs. The wild resources of MO play an important role in scientific studies and application since they have mainly experienced natural selection and are minimally influenced by artificial selection, however, they are on the verge of extinction at present. Most of MO are cultivated artificially for many years and have been propagated asexually mainly by cuttings, which may get easily infected with  nystose , 15. Ana nystose , ITS [17 nystose . These sSNP, as a representative of the third generation of molecular marker technology, has been widely used in the differentiation and identification of various plant and animal germplasm resources –22. RNA-Most researchers regard dispersal speciation and vicariance as the two major modes of the formation of plant and animal geographical patterns, such as the quaternary glacial and interglacial oscillations that have had an important influence on the different lineages evolution since populations of ice sheets isolated in distant refuges –28. ManeIn this study, we have extensively collected 88 germplasm resources of MO from ten populations across Guangdong, Guangxi, Fujian and Hainan provinces. The morphological, biochemical and molecular markers were used to comprehensively study the germplasm variation of MO. The aim was to obtain a complete description of genetic diversity of MO accessions came from different regions in China, discover and utilize various gene and genotype resources, search for excellent MO accessions, pave a way for the breeding of new varieties and protection of germplasm resources.The geographic distribution of 88 MO populations is shown in Fig. A higher H′ means a higher degree of genetic differentiation. In this study, the H′ of the nine phenotypic traits varied from 0.7930 to 2.0430, with an average of 1.7404. The leaf width (2.0430) and root range (1.9593) were most diverse within the set of MO accessions while the lowest was for the section color. The H′ of other traits was root diameter (1.9442) > lateral root number (1.9273) > root length (1.8977) > leaf length (1.8807) > main root number (1.7275) > plant height (1.4913).According to the investigation, the accessions of MO in Guangdong province could be divided into three categories: large leaf species, medium leaf species and small leaf species with significantly different phenotypic characteristics. Among them, the large leaf species with yellow-green, elliptic or long-elliptic leaves, which average length was up to 8.5 cm, and the leaves of medium leaf species were dark green, slightly round with an average length of 6.2 cm, while those of small leaf species were dark green and extremely narrow, just like willow leaves, with an average length of 5.5 cm. The number of roots, root length and diameter of small leaf species were larger so that the yield was higher obviously than other germplasms. In addition, we found a kind of modern landrace with purple buds, dark green and lighter leaves, which with more hairs. Most of them were short and the local called “Hei Rui Zai” with larger planting area. However, the same germplasm from different populations varied greatly in morphology, which might be because of the influence of ecological environment and local artificial intervention. For instance, the root length of Hei Rui Zai from Nanjing, Fujian could be as long as 104.60 cm, while that from Wuzhou, Guangxi was only 8.30 cm, and the root was very thin, which might be the result of the backward management level of Wuzhou and the infertile soil.Amomum villosum forest and has a large shade.The wild species from different populations also have large differences in morphology, such as those from Qinzhou and Fangcheng, Guangxi have long spindle shape, dark green, bright surface, less hair leaves, thinner roots, lavender section and longer vines, which wrap in the associated plants. We found a special wild plant in Fangcheng with an average leaf length of 10.3 cm and a leaf width of 4.9 cm, with an unusually bright, glabrous surface and black vines Fig. a. The wiF-furanosaccharide nystose, indicating that the feasibility of using these traits to breed new varieties with high active ingredients. However, we found that there was a negative correlation between root diameter and the content of nystose, indicating that the sample with a smaller root diameter has a higher content of nystose, which was in contradiction with the traditional grading standards. Moreover, the phenotypic traits such as leaf width, root length, root range, the main and lateral root number, as well as the content of 1F-furanosaccharide nystose were also positively correlated with the latitude and longitude, which suggested that the plantation site with high latitude and longitude is more suitable for the growth and development of MO. Finally, the root length, root range and the contents of oligosaccharides were significantly positively correlated with altitude, which provides scientific basis for the rational cultivation of MO.The content of oligosaccharides of MO is shown in Table F-furanosaccharide nystose. The section color contributed much to the PC4, which explained 9.825% of the total variation. All the 11 variables were slightly differentiated and it was found that they could be used to discriminate the MO accessions.Furthermore, PCA analysis revealed that the first four principal components explained 78.889% of the total diversity Fig. . The PC1Assessment of MO genetic diversity using nine phenotypic traits and two main chemical components revealed that 80 accessions were grouped into three distinct clusters Fig. S. The cluPutative SNP markers were identified in 88 MO accessions using GATK software. A total of 719,010 SNP markers were included across all libraries when the identified SNPs of all 88 MO samples were combined together, and 228,615 markers were considered good enough to estimate the genetic diversity and population structure of MO after those failing minor allele frequency test (MAF < 0.05) 490,395) were removed. The number of SNPs per sample ranged from 171,984 to 227,6322 with an average of 220,056, and the sample with the largest number of SNPs was FJ05, while the FJ20 with the smallest number. A total of 13,076,979 homozygous SNPs and 6,287,963 heterozygous SNPs were detected in all 88 accessions, accounting for 67.53 and 32.47% of the total number of SNPs, respectively. The average heterozygous rate was 32.26%  and transversion  were the two most abundant types of substitution, including 134,892 (59%) and 93,723 (41%) SNPs, respectively  classification was used to distinguish the available functions of the genes with non-synonymous SNPs or other SNPs that alter amino acid sequence based on sequence homology. A total of 43,202 genes were categorized into three main GO terms: biological processes, molecular function and cellular components Fig. , and theIS, FIT and FST values were calculated by STRUCTURE software to evaluate the population structure level. The FIS and FIT were ranged from − 0.97 to 0.87 and − 0.97 to 0.95, with the mean of − 0.40 and − 0.07, respectively. The higher value of FIS, which was measured at the subpopulation level of the entire population indicates that the populations lack heterozygosity and high specificity. The FST varied from 0 to 0.72 with an average of 0.24  was carried out to estimate the population genetic constitution using its reliability and consistency, which can provide some valuable information Table . The resThe genetic distances (GD) and genetic identity (GI) between ten populations were calculated based on the data of SNP locis, and the results showed that the genetic distances between Qinzhou and Danzhou and other populations were larger, which ranged from 0.0556 to 0.3229 with an average of 0.2269, while those between other populations were relatively smaller, only distributed between 0.0073 and 0.2915, with an average of 0.0968 (Table SThe unweighted pair group method using arithmetic average (UPGMA) phylogenetic tree was generated based on the genetic identity, and the result revealed that 88 MO accessions were mainly grouping in three clusters Fig. . The cluThe mixed Bayesian clustering model-based method in STRUCTURE analysis was used to determine the group of population. The results suggested that K (the randomly mating subgroups’ number) was equal to 3 as the optimal number of groups  equipped with an ELSD-UM5800 detector. The column was Waters XBridge™ Amide . The mobile phase consisted of 0.2% triethylamine acetonitrile (A) -0.2% triethylamine water (B), and the linear gradient was set as follows: 0–10 min for 75% A to 70% A, 10–20 min for 70% A, 20–45 min for 70% A to 60% A, 45–60 min for 60% A, and 60–63 min for 60% A to 75% A. The following parameters were also set: volume flow of 0.8 mL·min ·min− 1 .F-fructofuranosyl nystose) were purchased from Shanghai Yuanye Biotechnology Co., LTD . The lot numbers of standards are SS0905GA14, SA0418GA14, TF0226CA14, C09D8Q50061, Z17A9H59088, S09A8D41431, respectively, and the purity is greater than 98%. The samples were crushed, and 0.5 g of each sample was soaked in 50 mL of 50% ethanol solution. Ultrasonic extraction was performed for 20 min after half an hour of rest, and then centrifuged at 3000 rpm for 10 min. The upper layer was collected, filtered through at 0.22 μm microporous membrane filtration and then transferred for HPLC-ELSD analysis [Standards of oligosaccharide  following the manufacturer’s instructions. The quality and concentration of RNA samples were assessed with a Nanodrop spectrophotometer  and the integrity of RNA was determined using Agilent 2100 Bioanalyzer.The high-quality RNAs were used for cDNA library construction. Oligo (dT) labeled magnetic beads were used to combine the polyA of the mRNA for purifying the mRNA. The mRNA was fragmented with the size of 200–300 bp at elevated temperature in the presence of divalent cations and the first-strand cDNA is synthesized, and this cDNA was transformed into double-strand cDNA using DNA polymerase I and RnaseH. The cDNA was cleaned by AgencourtAmpure XP SPRI beads (Beckman-Coulter). The protruding termini of the DNA fragments were end-repaired and added “A” base, and adapters were ligated to the cDNA fragments. The sequencing library was constructed using 10 cycles of PCR. The concentration and size of the cDNA library were determined using Qubit 2.0 Fluorometer  and quantified with Agilent 2100 Bioanalyzer . Furthermore, all libraries were sequenced using the Illumina HiSeq 4000 platform with a paired-end reads length of 150 bp at Science Corporation of Gene  .Q < 20). The high quality reads were then de novo assembled into contigs and transcripts using the Trinity package (version 2.4.0) with the default parameters. The transcripts were clustered to reduce data redundancy by blasting against the nr protein database and the longest sequences in each cluster were reserved as unigenes.After the sequencing of the Illumina paired-end, raw reads were filtered by removal of adapter sequences, reads containing poly-Ns, and reads with a low-quality score  with default parameters . The picA Gene Ontology (GO) analysis was conducted to annotate the genes harboring non-synonymous SNPs with the MO nuclear genome used as background references. The AgriGO web tool was used to identify enriched GO terms and those with corrected-pvalue ≤0.05 were considered significantly enriched by the hypergeometric test.H′) index, Minor allele frequency (MAF), Observed heterozygosity (Ho), Expected heterozygosity (He), Observed number of alleles (Na), effective number of alleles (Ne), Nei’s gene diversity index (Nei), Shannon’s information index (I), The percentage of polymorphic bands (PPB), Fixity coefficient (Fst), Gene flow (Nm), Genetic identity (GI) and Genetic diversity (GD), they were estimated by PowerMarker 3.25 and Popgene version 1.32 software [H′is a basic index to measure the genetic diversity of population and was calculated as follows:H′is Shannon-Weaver index, Pi is the frequency of the ith variant type.Genetic diversity of the population is generally estimated by parameters, such as Shannon-Weaver  iterations of 100,000. The number of true clusters in the data (K) was determined by the CLUMPAK software. And the optimal K (the number of subpopulations) was estimated based on the posterior probability of the data for a given K, as well as the △K. Finally, the full search algorithm was used to align the replication results of the cluster analysis.To offer an additional support for the population structure and the number of populations of MO accessions, this study also carried out the PCA using Genome-wide Complex Trait Analysis (GCTA) software with default parameters . In ordeAdditional file 1.Additional file 2.Additional file 3.


Gigantidas childressi and Bathymodiolus heckerae.Deep-sea mussels in the subfamily Bathymodiolinae have unique adaptations to colonize hydrothermal-vent and cold-seep environments throughout the world ocean. These invertebrates function as important ecosystem engineers, creating heterogeneous habitat and promoting biodiversity in the deep sea. Despite their ecological significance, efforts to assess the diversity and connectivity of this group are extremely limited. Here, we present the first genomic-scale diversity assessments of the recently discovered bathymodioline cold-seep communities along the U.S. Atlantic margin, dominated by G. childressi. No evidence was found for genetic diversification across depth in G. childressi, likely due to their high dispersal capabilities. Kinship analyses indicated a high degree of relatedness among individuals, and at least 10–20% of local recruits within a particular site. We also discovered candidate adaptive loci in G. childressi and B. heckerae that suggest differences in developmental processes and depth-related and metabolic adaptations to chemosynthetic environments.A Restriction-site Associated DNA Sequencing (RADSeq) approach was used on 177 bathymodiolines to examine genetic diversity and population structure within and between seep sites. Assessments of genetic differentiation using single-nucleotide polymorphism (SNP) data revealed high gene flow among sites, with the shallower and more northern sites serving as source populations for deeper occurring These results highlight putative source communities for an important ecosystem engineer in the deep sea that may be considered in future conservation efforts. Our results also provide clues into species-specific adaptations that enable survival and potential speciation within chemosynthetic ecosystems.The online version contains supplementary material available at 10.1186/s12862-022-02027-4. Bathymodioline mussels that dominate many cold-seep communities serve as characteristic indicator fauna for methane and sulfide rich environments (reviewed in ). They tChemosynthetic cold seeps are numerous along the U.S. Atlantic margin , though Gigantidas childressi ).e seabed , 61, 73.Notably, our kinship results also suggested that at least 10 and 17% of individuals were related at both NCS and BRS, respectively. These percentages seem quite high for a random sampling of a relatively small portion of the sub-population at each site. One hypothesis that has been proposed to explain high occurrences of kin in settlement patches is the ‘sweepstakes reproductive success’, whereby relatively few individuals produce a majority of successful recruits due to stochastic processes –81. VariResults of our study indicated that 427 genes are potentially under selection between the bathymodioline species surveyed. Based on the KEGG annotations, many of these genes can be grouped under three primary protein functional families: (1) metabolism, (2) genetic information processing, and (3) signaling and cellular processes. These genomic differences are likely related to environmental adaptations of the two species combined with the endosymbiont repertoire that each species harbors. In addition, some genes associated with development were found as outliers, suggesting potential developmental differences between these bathymodioline species. Below we highlight some of these genes under the three protein families, particularly as they relate to environmental or chemosynthetic adaptations, but we provide the full list of 427 genes in Additional file G. platifrons indicated that several genes in the sulfide oxidation pathway, including sulfite oxidase, are upregulated in response to increased sulfide concentrations ), for the 427 unique bathymodioline genes corresponding to the outlier SNPs detected with pcadapt.Additional file 7. Figure S3. Reduced representation of the Gene Ontology (GO) Biological Process categories shown in Figure 6, and corresponding putative number of genes linked to each process, that are associated with the outlier SNPs identified with pcadapt.


Taken as a whole, psychiatric disorders are considered as complex genetic disorders. There are clear genetic mutations and susceptibility factors to these disorders. However, these form the full spectrum of impact, frequency, and mutation type. With rare large scale chromosomal rearrangements and copy number mutations of high impact at one end, and common single nucleotide variations of minor impact at the other. This multitude of variation type also means that different epidemiological study designs are needed to test the genetic component of these disorders, from familial forms, to common population level studies. This process has been facilitated by advances in genomic analysis, that enable the measuring of genetic variation at a greater depth in a greater number of individuals and has led to a boom in genetic information. This has given us a greater understanding of the genetic aetiology of psychiatric disorders and how they are biologically related to each other. How this information can be translated to the clinics, can now be considered. Genetic testing in psychiatric disorders, is currently possible for certain disorders and mutation types, but is not universally advised. Much still remains to be understood about population level genetic risk factors before they could conceivably be utilised in the clinic. Whereas genetic testing of high impact mutations could be of use to the clinical programs, and are actively tested for in clinics across Europe.No significant relationships.


Mycobacterium tuberculosis (MTB) isolates worldwide and determined the minimum inhibitory concentration (MIC) on a grid of 2-fold concentration dilutions for 13 antimicrobials using quantitative microtiter plate assays. We performed oligopeptide- and oligonucleotide-based genome-wide association studies using linear mixed models to discover resistance-conferring mechanisms not currently catalogued. Use of MIC over binary resistance phenotypes increased sample heritability for the new and repurposed drugs by 26% to 37%, increasing our ability to detect novel associations. For all drugs, we discovered uncatalogued variants associated with MIC, including in the Rv1218c promoter binding site of the transcriptional repressor Rv1219c (isoniazid), upstream of the vapBC20 operon that cleaves 23S rRNA (linezolid) and in the region encoding an α-helix lining the active site of Cyp142 . We observed that artefactual signals of cross-resistance could be unravelled based on the relative effect size on MIC. Our study demonstrates the ability of very large-scale studies to substantially improve our knowledge of genetic variants associated with antimicrobial resistance in M. tuberculosis.The emergence of drug-resistant tuberculosis is a major global public health concern that threatens the ability to control the disease. Whole-genome sequencing as a tool to rapidly diagnose resistant infections can transform patient treatment and clinical practice. While resistance mechanisms are well understood for some drugs, there are likely many mechanisms yet to be uncovered, particularly for new and repurposed drugs. We sequenced 10,228  The emergence of drug resistant tuberculosis is a major global public health concern that threatens the ability to control the disease. Phenotyping and sequencing 10,000 Mycobacterium tuberculosis genomes identifies previously uncatalogued genetic variants associated with resistance to thirteen new and repurposed, second line and first line drugs. Tuberculosis (TB) continues to represent a major threat to global public health, with the World Health Organization (WHO) estimating 10 million cases and 1.4 million deaths in 2019 alone ,4; howevUnderstanding mechanisms of resistance in TB is important for developing rapid susceptibility tests that improve individual patient treatment, recommending drug regimens that reduce the development of MDR and developing new and improved drugs that expand treatment options ,9. GenomMycobacterium tuberculosis makes it difficult to pinpoint resistance variants unless they arise on multiple genetic backgrounds, reiterating the need for large sample sizes. Sophisticated analyses are required that attempt to disentangle genetic causation from correlation ), scientific committee of the Adolfo Lutz Institute (CTC-IAL 47-J/2017), and in the Ethics Committee (CAAE: 81452517.1.0000.0059) and Ethics Committee review by Universidad Peruana Cayetano Heredia  and LSHTM .CRyPTIC collected isolates from 27 countries worldwide, oversampling for drug resistance, as described in detail in . Clinica6 or > 5 × 106; (iv) number of unique oligonucleotides < 3.5 × 106 or > 5 × 106; and (v) sequencing read length not 150/151 bases long. This gave a GWAS dataset of 10,422 genomes used to create the variant presence/absence matrices. We used Mykrobe [Mycobacterium genomes not belonging to lineages 1 to 4 or representing mixtures of lineages. This led to the exclusion of 193 genomes, which were removed from GWAS by setting the phenotypes to NA. The number of genomes with a high-quality phenotype for at least 1 of the 13 drugs was therefore 10,228. Of these, 533 were lineage 1; 3,581 were lineage 2; 805 were lineage 3; and 5,309 were lineage 4. Due to rigorous quality control described above, only samples with high-quality phenotypes were tested for each drug, resulting in a range of 6,388 to 9,418 genomes used in each GWAS. The log2 MIC phenotypes used in the study are available in S2 Data, and the data is publicly available for download via an FTP site at the European Bioinformatics Institute (https://ftp.ebi.ac.uk/pub/databases/cryptic/release_june2022/pubs/gwas2022).A total of 15,211 isolates were included in the initial CRyPTIC dataset with both genomes and phenotype measurements after passing genome quality control filters ,78; howe Mykrobe  to identA pairwise distance matrix was constructed for the full CRyPTIC dataset based on variant calls . For vis9, then the reads were randomly subsampled prior to assembly down to a sequence length of 1 × 109, which is around 227× mean coverage. For the oligopeptide analysis, each assembly contig was translated into the 6 possible reading frames in order to be agnostic to the correct reading frame. A total of 11 amino acid long oligopeptides were counted in a 1 amino acid sliding window from these translated contigs. The 31-bp nucleotide oligonucleotides were also counted from the assembled contigs using dsk [To capture SNP-based variation, indels, and combinations of SNPs and indels, we pursued oligonucleotide and oligopeptide-based approaches, focusing primarily on oligopeptides. Where helpful for clarifying results, we interpreted significant associations using oligonucleotides. Sequence reads were assembled de novo using Velvet Optimiser  with a ssing dsk . For botWe used the surrounding context of the contigs that the oligopeptides/oligonucleotides were identified in to assist with their alignment. First, we aligned the contigs of each genome to the H37Rv reference genome  using nuIsolates were sampled from 9 sites and MICs were measured on 2 versions of the quantitative microtiter plate assays, UKMYC5 and UKMYC6 . UKMYC6 r2) of the most significant oligopeptide or nucleotide in the gene with all other top oligopeptides or nucleotides for the top 20 genes for the drug. The top variants in the genes noted were not in high LD with known causal variants, in some cases they were in LD with other top 20 gene hits that were less significant.We performed association testing using LMM analyses implemented in the software GEMMA to control for population structure . Signifip-value was smaller than α/np, where we took α = 0.05 to be the genome-wide false positive rate ) and np to be the number of unique phylopatterns above 0.1% MAF in the genomes tested for the particular drug. The −log10p significance thresholds for the oligopeptide analyses were: 7.69 , 7.65 (bedaquiline), 7.64 , 7.67 , 7.62 , 7.70 (isoniazid), 7.60 (moxifloxacin), 7.71 (rifabutin), and 7.68 (rifampicin). The −log10p significance thresholds for the oligonucleotide analyses were: 7.38 , 7.34 , 7.36 , 7.32 (ethambutol), 7.39 , 7.33 (linezolid), 7.31 (moxifloxacin), and 7.37 (rifampicin).Multiple testing was accounted for by applying a Bonferroni correction calculated for each drug. The unit of correction for all studies was the number of unique “phylopatterns,” i.e., the number of unique partitions of individuals according to variant presence/absence for the phenotype tested. An oligopeptide/oligonucleotide was considered to be significant if its Sample heritability is the proportion of the phenotypic variation that can be explained by the bacterial genotype assuming additive effects. This was estimated using the LMM null model in GEMMA  from theConceptualisation: Camilla Rodrigues, David Moore, Derrick W. Crook, Daniela M. Cirillo, Philip W Fowler, Zamin Iqbal, Nazir A. Ismail, Nerges Mistry, Stefan Niemann, Tim E.A. Peto, Guy Thwaites, A. Sarah Walker, Timothy M Walker, Daniel J. WilsonMethodology: Sarah G. Earle, Daniel J. Wilson, Clara Grazian, A Sarah WalkerSoftware: Sarah G. Earle, Daniel J. WilsonFormal analysis: Sarah G. Earle, Daniel J. Wilson, Clara Grazian, A Sarah WalkerInvestigation: The CRyPTIC ConsortiumResources: The CRyPTIC ConsortiumData curation: Martin Hunt, Jeff Knaggs, Zamin Iqbal, Philip W Fowler, Zamin IqbalWriting – original draft preparation: Sarah G. Earle, Daniel J. Wilson, A Sarah Walker, Philip W FowlerWriting – review & editing: The CRyPTIC ConsortiumVisualization: Sarah G. EarleSupervision: Daniela M Cirillo, Derrick W. Crook, Tim E.A. Peto, Daniel J. Wilson, A Sarah Walker, Zamin Iqbal, Philip W FowlerProject administration: The CRyPTIC Consortium;Funding acquisition: Camilla Rodrigues, David Moore, Derrick W. Crook, , Daniela M. Cirillo, Zamin Iqbal, Nazir A. Ismail, Nerges Mistry, Stefan Niemann, Tim E.A. Peto, Guy Thwaites, A. Sarah Walker, Timothy M Walker, Daniel J. WilsonS1 Data(XLSX)Click here for additional data file.S2 Data(XLSX)Click here for additional data file.S1 Acknowledgements(DOCX)Click here for additional data file.S1 FigThe red dashed line indicates the ECOFF, measurements to the left of the ECOFF are considered sensitive, and those to the right are considered resistant. AMI, amikacin; BDQ, bedaquiline; CFZ, clofazimine; DLM, delamanid; ECOFF, epidemiological cutoff; EMB, ethambutol; ETH, ethionamide; GWAS, genome-wide association studies; INH, isoniazid; KAN, kanamycin; LEV, levofloxacin; LZD, linezolid; MIC, minimum inhibitory concentration; MXF, moxifloxacin; RFB, rifabutin; RIF, rifampicin.(PDF)Click here for additional data file.S2 FigSample heritability estimates and 95% CIs are shown for the 13 drugs, DLM, CFZ, LZD), BDQ, MXF, LEV, KAN, EMB, ETH, AMI, RIF, INH, and RFB. When estimating heritability of the same phenotype, the oligopeptide and oligonucleotide estimates are very similar. AMI, amikacin; BDQ, bedaquiline; CI, confidence interval; CFZ, clofazimine; DLM, delamanid; EMB, ethambutol; ETH, ethionamide; INH, isoniazid; KAN, kanamycin; LEV, levofloxacin; LZD, linezolid; MIC, minimum inhibitory concentration; MXF, moxifloxacin; RFB, rifabutin; RIF, rifampicin.(PDF)Click here for additional data file.S3 Figp-values to the expected distribution under the null hypothesis for the drugs AMI, BDQ, CFZ, DLM, EMB, ETH, INH, and KAN. Oligopeptides in the orange (MAF < 0.1%) were not initially analysed, only used for signal interpretation. AMI, amikacin; BDQ, bedaquiline; CFZ, clofazimine; DLM, delamanid; EMB, ethambutol; ETH, ethionamide; INH, isoniazid; KAN, kanamycin; MAF, minor allele frequency.Comparing the empirical distribution of (PDF)Click here for additional data file.S4 Figp-values to the expected distribution under the null hypothesis for the KAN, LEV, LZD, MXF, RFB, and RIF. Oligopeptides in the orange (MAF < 0.1%) were not initially analysed, only used for signal interpretation. KAN, kanamycin; LEV, levofloxacin; LZD, linezolid; MAF, minor allele frequency; MXF, moxifloxacin; RFB, rifabutin; RIF, rifampicin.Comparing the empirical distribution of (PDF)Click here for additional data file.S5 FigFor many of the drugs, the most significant oligopeptides were associated with lower MIC. AMI, amikacin; BDQ, bedaquiline; CFZ, clofazimine; DLM, delamanid; EMB, ethambutol; ETH, ethionamide; INH, isoniazid; KAN, kanamycin; LEV, levofloxacin; LZD, linezolid; MIC, minimum inhibitory concentration; MXF, moxifloxacin; RFB, rifabutin; RIF, rifampicin.(PDF)Click here for additional data file.S6 FigOn the left, the beta estimates are shown for all significant oligopeptides for the drugs the gene is causal for, on the right, the beta estimates are shown for the same gene, but for the drugs they are artefactually associated to. For many drugs, the beta estimate is lower when the gene is significant due to artefactual cross-resistance. Drug name abbreviations are as follows: AMI, BDQ, CFZ, DLM, EMB, ETH, INH, KAN, LEV, LZD, MXF, RFB, and RIF. AMI, amikacin; BDQ, bedaquiline; CFZ, clofazimine; DLM, delamanid; EMB, ethambutol; ETH, ethionamide; INH, isoniazid; KAN, kanamycin; LEV, levofloxacin; LZD, linezolid; MXF, moxifloxacin; RFB, rifabutin; RIF, rifampicin.(PDF)Click here for additional data file.S7 FigspoU coding region A ethambutol and B rifampicin, and oligonucleotide alignment plots showing close-ups of the significant region just downstream of spoU for C ethambutol and D rifampicin. The black dashed lines indicate the Bonferroni-corrected significance thresholds. In the Manhattan plots, oligopeptides are coloured by the reading frame that they align to, black for the correct reading frame for spoU. Oligopeptides assigned to the region but did not align using BLAST are shown in grey on the right-hand side of the plots. In the oligonucleotide alignment plots, the H37Rv reference codons are shown at the bottom of the figure, grey for an invariant site, coloured at variant site positions. The oligonucleotides that aligned to the region are plotted from least significant at the bottom to most significant at the top. The background colour of the oligonucleotides represents the direction of the b estimate, light grey when b < 0 (associated with lower MIC), dark grey when b > 0 (associated with higher MIC). Oligonucleotides are coloured by their amino acid residue at all variant positions. Oligonucleotides below the MAF threshold and not included in the analysis, but visualised here for signal interpretation, are marked by *s. The spoU stop codon is highlighted in red in the alignment plots. EMB, ethambutol; MAF, minor allele frequency; MIC, minimum inhibitory concentration; RIF, rifampicin.Manhattan plots showing the oligopeptide association results for the (PDF)Click here for additional data file.S8 FigRv1219c coding region for the A oligopeptides and B oligonucleotides, and oligopeptide alignment plots showing close-ups of the significant region in Rv1219c for C oligopeptides present in 5 or more genomes in the full GWAS dataset and D oligopeptides present in at least 1 genome in the full GWAS dataset. The black dashed lines indicate the Bonferroni-corrected significance thresholds. In the Manhattan plots, oligopeptides are coloured by the reading frame that they align to, black for the correct reading frame for Rv1219c. Oligopeptides and nucleotides assigned to the region but did not align using BLAST are shown in grey on the right-hand side of the plots. In the oligopeptide alignment plots, the H37Rv reference codons are shown at the bottom of the figure, grey for an invariant site, coloured at variant site positions. The oligopeptides that aligned to the region are plotted from least significant at the bottom to most significant at the top. The background colour of the oligopeptides represents the direction of the b estimate, light grey when b < 0 (associated with lower MIC), dark grey when b > 0 (associated with higher MIC). Oligopeptides are coloured by their amino acid residue at all variant positions. Oligopeptides and nucleotides below the MAF threshold and not included in the analysis, but visualised here for signal interpretation, are marked by *s. GWAS, genome-wide association studies; MAF, minor allele frequency; MIC, minimum inhibitory concentration.Manhattan plots showing the association results for the (PDF)Click here for additional data file.S9 FigPPE42 coding region A amikacin and B kanamycin, and oligopeptide alignment plots showing close-ups of the significant region in PPE42 for C amikacin and D kanamycin. Black dashed lines indicate the Bonferroni-corrected significance thresholds. In the Manhattan plots, oligopeptides are coloured by the reading frame that they align to, black for the correct reading frame for PPE42. Oligopeptides assigned to the region but did not align using BLAST are shown in grey on the right-hand side of the plots. In the oligopeptide alignment plots, the H37Rv reference codons are shown at the bottom of the figure, grey for an invariant site, coloured at variant site positions. The oligopeptides that aligned to the region are plotted from least significant at the bottom to most significant at the top. The background colour of the oligopeptides represents the direction of the b estimate, light grey when b < 0 (associated with lower MIC), dark grey when b > 0 (associated with higher MIC). Oligopeptides are coloured by their amino acid residue at all variant positions. Oligopeptides below the MAF threshold and not included in the analysis, but visualised here for signal interpretation, are marked by *s. AMI, amikacin; KAN, kanamycin; MAF, minor allele frequency; MIC, minimum inhibitory concentration.Manhattan plots showing the oligopeptide association results for the (PDF)Click here for additional data file.S10 FigwhiB7 for the A oligopeptides and B oligonucleotides, and alignment plots showing close-ups of significant regions in whib7 for C oligopeptides in the C-terminal end of the coding region and D oligonucleotides in the upstream intergenic region. The black dashed lines indicate the Bonferroni-corrected significance thresholds. In the Manhattan plots, oligopeptides are coloured by the reading frame that they align to, black for the correct reading frame for whiB7. Oligopeptides and nucleotides assigned to the region but did not align using BLAST are shown in grey on the right-hand side of the plots. In the alignment plots, the H37Rv reference codons are shown at the bottom of the figure, grey for an invariant site, coloured at variant site positions. The oligopeptides and nucleotides that aligned to the region are plotted from least significant at the bottom to most significant at the top. The background colour of the oligopeptides and nucleotides represents the direction of the b estimate, light grey when b < 0 (associated with lower MIC), dark grey when b> 0 (associated with higher MIC). Oligopeptides and nucleotides are coloured by their allele at all variant positions. Oligopeptides and nucleotides below the MAF threshold and not included in the analysis, but visualised here for signal interpretation, are marked by *s. MAF, minor allele frequency; MIC, minimum inhibitory concentration.Manhattan plots showing the association results for (PDF)Click here for additional data file.S11 FigtlyA coding region for the A oligopeptides and B oligonucleotides, and alignment plots showing close-ups of the significant region in tlyA for the C oligopeptides and D oligonucleotides. The black dashed lines indicate the Bonferroni-corrected significance thresholds; no oligonucleotides were significant in this region. In the Manhattan plots, oligopeptides are coloured by the reading frame that they align to, black for the correct reading frame for tlyA. Oligopeptides and nucleotides assigned to the region but did not align using BLAST are shown in grey on the right-hand side of the plots. In the alignment plots, the H37Rv reference alleles are shown at the bottom of the figure, grey for an invariant site, coloured at variant site positions. The oligopeptides and nucleotides that aligned to the region are plotted from least significant at the bottom to most significant at the top. The background colour of the oligopeptides and nucleotides represents the direction of the b estimate, light grey when b < 0 (associated with lower MIC), dark grey when b> 0 (associated with higher MIC). Oligopeptides and nucleotides are coloured by their allele at all variant positions. Oligopeptides and nucleotides below the MAF threshold and not included in the analysis, but visualised here for signal interpretation, are marked by *s. MAF, minor allele frequency; MIC, minimum inhibitory concentration.Manhattan plots showing the association results for the (PDF)Click here for additional data file.S12 FigAcysA2 and B cysA3, and oligonucleotide alignment plots showing close-ups of the significant region for CcysA2 and DcysA3. The black dashed lines indicate the Bonferroni-corrected significance thresholds. The significant oligonucleotides that align to cysA2 and cysA3 are the same. In the Manhattan plots, oligopeptides are coloured by the reading frame that they align to, black for the correct reading frame for cysA2 or cysA3. Oligopeptides assigned to the region but did not align using BLAST are shown in grey on the right-hand side of the plot. In the oligonucleotide alignment plots, the H37Rv reference alleles are shown at the bottom of the figure, grey for an invariant site, coloured at variant site positions. The oligonucleotides that aligned to the region are plotted from least significant at the bottom to most significant at the top. The background colour of the oligonucleotides represents the direction of the b estimate, light grey when b < 0 (associated with lower MIC), dark grey when b > 0 (associated with higher MIC). Oligonucleotides are coloured by their allele at all variant positions. Oligonucleotides below the MAF threshold and not included in the analysis, but visualised here for signal interpretation, are marked by *s. The region that encodes the rhodanese characteristic signature in the N-terminal region is highlighted in red in the alignment plots. MAF, minor allele frequency; MIC, minimum inhibitory concentration.Manhattan plots showing the association results for the coding region for (PDF)Click here for additional data file.S13 FigamiA2/era coding region for the A oligopeptides and B oligonucleotides, and oligonucleotide alignment plots showing close-ups of the significant region in amiA2/era in the correct reading frame for CamiA2 and Dera. The black dashed lines indicate the Bonferroni-corrected significance thresholds. In the Manhattan plots, oligopeptides are coloured by the reading frame that they align to, black for the correct reading frame for amiA2. Oligopeptides and nucleotides assigned to the region but did not align using BLAST are shown in grey on the right-hand side of the plots. In the oligonucleotide alignment plots, the H37Rv reference alleles are shown at the bottom of the figure, grey for an invariant site, coloured at variant site positions. The oligonucleotides that aligned to the region are plotted from least significant at the bottom to most significant at the top. The background colour of the oligonucleotides represents the direction of the b estimate, light grey when b < 0 (associated with lower MIC), dark grey when b > 0 (associated with higher MIC). Oligonucleotides are coloured by their allele at all variant positions. Oligonucleotides below the MAF threshold and not included in the analysis, but visualised here for signal interpretation, are marked by *s. MAF, minor allele frequency; MIC, minimum inhibitory concentration.Manhattan plots showing the association results for the (PDF)Click here for additional data file.S14 Figcyp142 coding region for the A oligopeptides and B oligonucleotides, and alignment plots showing close-ups of the significant region in cyp142 for the C oligopeptides and D oligonucleotides. The black dashed lines indicate the Bonferroni-corrected significance thresholds. In the Manhattan plots, oligopeptides are coloured by the reading frame that they align to, red for the correct reading frame for cyp142. Oligopeptides and nucleotides assigned to the region but did not align using BLAST are shown in grey on the right-hand side of the plots. In the alignment plots, the H37Rv reference alleles are shown at the bottom of the figure, grey for an invariant site, coloured at variant site positions. The oligopeptides and nucleotides that aligned to the region are plotted from least significant at the bottom to most significant at the top. The background colour of the oligopeptides and nucleotides represents the direction of the b estimate, light grey when b < 0 (associated with lower MIC), dark grey when b > 0 (associated with higher MIC). Oligopeptides and nucleotides are coloured by their allele at all variant positions. Oligopeptides and nucleotides below the MAF threshold and not included in the analysis, but visualised here for signal interpretation, are marked by *s. MAF, minor allele frequency; MIC, minimum inhibitory concentration.Manhattan plots showing the association results for the (PDF)Click here for additional data file.S15 FigpknH coding region for the A oligopeptides and B oligonucleotides, and alignment plots showing close-ups of the significant region in pknH for the C oligopeptides and D oligonucleotides. The black dashed lines indicate the Bonferroni-corrected significance thresholds. In the Manhattan plots, oligopeptides are coloured by the reading frame that they align to, black for the correct reading frame for pknH. Oligopeptides and nucleotides assigned to the region but did not align using BLAST are shown in grey on the right-hand side of the plots. In the alignment plots, the H37Rv reference alleles are shown at the bottom of the figure, grey for an invariant site, coloured at variant site positions. The oligopeptides and nucleotides that aligned to the region are plotted from least significant at the bottom to most significant at the top. The background colour of the oligopeptides and nucleotides represents the direction of the b estimate, light grey when b < 0 (associated with lower MIC), dark grey when b > 0 (associated with higher MIC). Oligopeptides and nucleotides are coloured by their allele at all variant positions. Oligopeptides and nucleotides below the MAF threshold and not included in the analysis, but visualised here for signal interpretation, are marked by *s. MAF, minor allele frequency; MIC, minimum inhibitory concentration.Manhattan plots showing the association results for the (PDF)Click here for additional data file.S16 FigvapB20 for the A oligopeptides and B oligonucleotides, and C oligonucleotide alignment plot showing a close-up of the significant region just upstream of vapB20. The black dashed lines indicate the Bonferroni-corrected significance thresholds. In the Manhattan plots, oligopeptides are coloured by the reading frame that they align to, black for the correct reading frame for amiA2. Oligopeptides and nucleotides assigned to the region but did not align using BLAST are shown in grey on the right-hand side of the plots. In the oligonucleotide alignment plot, the H37Rv reference alleles are shown at the bottom of the figure, grey for an invariant site, coloured at variant site positions. The oligonucleotides that aligned to the region are plotted from least significant at the bottom to most significant at the top. The background colour of the oligonucleotides represents the direction of the b estimate, light grey when b < 0 (associated with lower MIC), dark grey when b > 0 (associated with higher MIC). Oligonucleotides are coloured by their allele at all variant positions. Oligopeptides and nucleotides below the MAF threshold and not included in the analysis, but visualised here for signal interpretation, are marked by *s. MAF, minor allele frequency; MIC, minimum inhibitory concentration.Manhattan plots showing the association results for (PDF)Click here for additional data file.S1 TableSample heritability estimates and 95% CIs are shown for the 13 drugs. CI, confidence interval; MIC, minimum inhibitory concentration.(PDF)Click here for additional data file.