Ranajit Das

Localizing Ashkenazic Jews to Primeval Villages in the Ancient Iranian Lands of Ashkenaz

The Yiddish language is over 1,000 years old and incorporates German, Slavic, and Hebrew elements. The prevalent view claims Yiddish has a German origin, whereas the opposing view posits a Slavic origin with strong Iranian and weak Turkic substrata. One of the major difficulties in deciding between these hypotheses is the unknown geographical origin of Yiddish speaking Ashkenazic Jews (AJs). An analysis of 393 Ashkenazic, Iranian, and mountain Jews and over 600 non-Jewish genomes demonstrated that Greeks, Romans, Iranians, and Turks exhibit the highest genetic similarity with AJs. The Geographic Population Structure analysis localized most AJs along major primeval trade routes in northeastern Turkey adjacent to primeval villages with names that may be derived from “Ashkenaz.” Iranian and mountain Jews were localized along trade routes on the Turkey’s eastern border. Loss of maternal haplogroups was evident in non-Yiddish speaking AJs. Our results suggest that AJs originated from a Slavo-Iranian confederation, which the Jews call “Ashkenazic” (i.e., “Scythian”), though these Jews probably spoke Persian and/or Ossete. This is compatible with linguistic evidence suggesting that Yiddish is a Slavic language created by Irano-Turko-Slavic Jewish merchants along the Silk Roads as a cryptic trade language, spoken only by its originators to gain an advantage in trade. Later, in the 9th century, Yiddish underwent relexification by adopting a new vocabulary that consists of a minority of German and Hebrew and a majority of newly coined Germanoid and Hebroid elements that replaced most of the original Eastern Slavic and Sorbian vocabularies, while keeping the original grammars intact.

Reconstructing Druze population history

The Druze are an aggregate of communities in the Levant and Near East living almost exclusively in the mountains of Syria, Lebanon and Israel whose ~1000 year old religion formally opposes mixed marriages and conversions. Despite increasing interest in genetics of the population structure of the Druze, their population history remains unknown. We investigated the genetic relationships between Israeli Druze and both modern and ancient populations. We evaluated our findings in light of three hypotheses purporting to explain Druze history that posit Arabian, Persian or mixed Near Eastern-Levantine roots. The biogeographical analysis localised proto-Druze to the mountainous regions of southeastern Turkey, northern Iraq and southeast Syria and their descendants clustered along a trajectory between these two regions. The mixed Near Eastern–Middle Eastern localisation of the Druze, shown using both modern and ancient DNA data, is distinct from that of neighbouring Syrians, Palestinians and most of the Lebanese, who exhibit a high affinity to the Levant. Druze biogeographic affinity, migration patterns, time of emergence and genetic similarity to Near Eastern populations are highly suggestive of Armenian-Turkish ancestries for the proto-Druze.

The Origins of Ashkenaz, Ashkenazic Jews, and Yiddish

Recently, the geographical origins of Ashkenazic Jews (AJs) and their native language Yiddish were investigated by applying the Geographic Population Structure (GPS) to a cohort of exclusively Yiddish-speaking and multilingual AJs. GPS localized most AJs along major ancient trade routes in northeastern Turkey adjacent to primeval villages with names that resemble the word “Ashkenaz.” These findings were compatible with the hypothesis of an Irano-Turko-Slavic origin for AJs and a Slavic origin for Yiddish and at odds with the Rhineland hypothesis advocating a Levantine origin for AJs and German origins for Yiddish. We discuss how these findings advance three ongoing debates concerning (1) the historical meaning of the term “Ashkenaz;” (2) the genetic structure of AJs and their geographical origins as inferred from multiple studies employing both modern and ancient DNA and original ancient DNA analyses; and (3) the development of Yiddish. We provide additional validation to the non-Levantine origin of AJs using ancient DNA from the Near East and the Levant. Due to the rising popularity of geo-localization tools to address questions of origin, we briefly discuss the advantages and limitations of popular tools with focus on the GPS approach. Our results reinforce the non-Levantine origins of AJs.

Unraveling the Population History of Indian Siddis

Abstract The Siddis are a unique Indian tribe of African, South Asian, and European ancestry. While previous investigations have traced their ancestral origins to the Bantu populations from subSaharan Africa, the geographic localization of their ancestry has remained elusive. Here, we performed biogeographical analysis to delineate the ancestral origin of the Siddis employing an admixture based algorithm, Geographical Population Structure (GPS). We evaluated the Siddi genomes in reference to five African populations from the 1000 Genomes project, two Bantu groups from the Human Genome Diversity Panel (HGDP) and five South Indian populations. The Geographic Population Structure analysis localized the ancestral Siddis to Botsawana and its present-day northeastern border with Zimbabwe, overlapping with one of the principal areas of secondary Bantu settlement in southeast Africa. Our results further indicated that while the Siddi genomes are significantly diverged from that of the Bantus, they manifested the highest genomic proximity to the North-East Bantus and the Luhyas from Kenya. Our findings resonate with evidences supporting secondary Bantu dispersal routes that progressed southward from the east African Bantu center, in the interlacustrine region and likely brought the ancestral Siddis to settlement sites in south and southeastern Africa from where they were disseminated to India, by the Portuguese. We evaluated our results in the light of existing historical, linguistic and genetic evidences, to glean an improved resolution into the reconstruction of the distinctive population history of the Siddis, and advance our knowledge of the demographic factors that likely contributed to the contemporary Siddi genomes.

Ancient ancestry informative markers for identifying fine-scale ancient population structure in Eurasians

The rapid accumulation of ancient human genomes from various places and time periods, mainly from the past 15,000 years, allows us to probe the past with an unparalleled accuracy and reconstruct trends in human biodiversity. Alongside providing novel insights into the population history, population structure permits correcting for population stratification, a practical concern in gene mapping in association studies. However, it remains unclear which markers best capture ancient population structure as not all markers are equally informative. Moreover, the high missingness rates in ancient, oftentimes haploid, DNA, may distort the population structure and prohibit genomic comparisons. In past studies, ancestry informative markers (AIMs) were harnessed to address such problems, yet whether AIMs finding methods are applicable to aDNA remains unclear. Here, we define ancient AIM (aAIMs) and develop a framework to evaluate established and novel AIMs-finding methods. We show that a novel principal component analysis (PCA)-based method outperforms all methods in capturing ancient population structure and identifying admixed individuals. Our results highlight important features of the genetic structure of ancient Eurasians and the choice of strategies to identify informative markers. This work can inform the design and interpretation of population and medical studies employing ancient DNA. Author summary Ancient DNA studies aim to identify geographical origin, migration routes, and disease susceptibility genes through the analysis of genetic markers such as single nucleotide polymorphisms (SNPs) in growing cohorts of ancient data. In addition to the existence of sub-structure in the studied population (i.e., differences in ancestry), ancient DNA suffers from high missingness rates and is oftentimes haploid, which may distort the inferred population structure and lead to spurious results. It is thereby imperative to address this possible bias by identifying the most accurate population structure. Due to the success of past studies in addressing similar problems using ancestry informative markers (AIMs), we defined ancient ancestry informative markers (aAIMs) that like AIMs can be used to interrogate ancient population structure. To find aAIMs, we designed a framework to evaluate established and novel AIMs-finding methods. We developed a database of 150,278 autosomal SNPs from 302 ancient genomes and 21 populations recovered from Europe, the Middle East, and North Eurasia dated to time periods from 14,000 to 1,500 years ago. We then applied two existing and three novel AIMs-finding methods and compared their performances against the complete dataset. We found that a novel principal component analysis (PCA)-based method captured the ancient population structure most accurately. Importantly, we introduce here a novel concept of aAIMs, a novel method that effectively identifies aAIMs, and a framework to compare the performances of AIMs. The outcome of our studies can improve the accuracy of genetic studies employing ancient DNA.

Phenetic classification of Kimmeridgian ammonites from the eastern Kachchh Basin, India

Thirty Kimmeridgian (Upper Jurassic) ammonite specimens of the genera Torquatisphinctes, Pachysphinctes, Katroliceras, and Indodichotomoceras collected from two horizons in the eastern part of the Kachchh Basin were phenetically classified. First, 23 morphological characters were selected for the analysis. The difference matrix was generated by treating the characters as a binary system (0 or 1) and giving scores between 0 and 2. The dendrogram, prepared using the R program, shows perfect groupings of the different taxa identified earlier through a traditional taxonomic approach. The percentage of shared characters has helped choosing significant characters to be used in distinguishing three major groups and one subgroup, which also validates the visual identification of the ammonite taxa. Categorization of the ammonites was also subjected to a Mann-Whitney U test to verify the results. Overall, the dendrogram depicted three distinct clusters, the Torquatisphinctes, Pachysphinctes, and Katroliceras groups. The specimens of Indodichotomoceras (designated the Indodichotomoceras subgroup) were clustered within the Torquatisphinctes group potentially because of their biplicate ornamentation and presence of constrictions. However, the Indodichotomoceras subgroup maintained its identity because of the thickness of the primary and secondary ribs.

An Ancestry Informative Marker Set Which Recapitulates the Known Fine Structure of Populations in South Asia

Abstract The inference of genomic ancestry using ancestry informative markers (AIMs) can be useful for a range of studies in evolutionary genetics, biomedical research, and forensic analyses. However, the determination of AIMs for highly admixed populations with complex ancestries has remained a formidable challenge. Given the immense genetic heterogeneity and unique population structure of the Indian subcontinent, here we sought to derive AIMs that would yield a cohesive and faithful understanding of South Asian genetic origins. To discern the most optimal strategy for extracting AIMs for South Asians we compared three commonly used AIMs-determining methods namely, Infocalc, FST, and Smart Principal Component Analysis with ADMIXTURE, using previously published whole genome data from the Indian subcontinent. Our findings suggest that the Infocalc approach is likely most suitable for delineation of South Asian AIMs. In particular, Infocalc-2,000 (N = 2,000) appeared as the most informative South Asian AIMs panel that recapitulated the finer structure within South Asian genomes with high degree of sensitivity and precision, whereas a negative control with an equivalent number of randomly selected markers when used to interrogate the South Asian populations, failed to do so. We discuss the utility of all approaches under evaluation for AIMs derivation and interpreting South Asian genomic ancestries. Notably, this is the first report of an AIMs panel for South Asian ancestry inference. Overall these findings may aid in developing cost-effective resources for large-scale demographic analyses and foster expansion of our knowledge of human origins and disease, in the South Asian context.

Tracing the biogeographical origin of South Asian populations using DNA SatNav

The Indian subcontinent includes India, Bangladesh, Pakistan, Nepal, Bhutan, and Sri Lanka that collectively share common anthropological and cultural roots. Given the enigmatic population structure, complex history and genetic heterogeneity of populations from this region, their biogeographical origin and history remain a fascinating question. In this study we carried out an in-depth genetic comparison of the five South Asian populations available in the 1000 Genomes Project, namely Gujarati Indians from Houston, Texas (GIH), Punjabis from Lahore (PJL), Indian Telugus from UK (ITU), Sri Lankan Tamils from UK (STU) and Bengalis from Bangladesh (BEB), tracing their putative biogeographical origin using a DNA SatNav algorithm - Geographical Population Structure (GPS). GPS positioned >70% of GIH and PJL genomes in North India and >80% of ITU and STU samples in South India. All South Asian genomes appeared to be assigned with reasonable accuracy, along trade routes that thrived in the ancient Mauryan Empire, which had played a significant role in unifying the Indian subcontinent and in the process brought the ancient North and South Indian populations in close proximity, promoting admixture between them, ~2300 years before present (YBP). Our findings suggest that the genetic admixture between ancient North and South Indian populations likely first occurred along the Godavari and Krishna river basin in Central-South India. Finally our biogeographical analyses provide critical insights into the population history and sociocultural forces driving migration patterns that may have been instrumental in shaping the population structure of the Indian subcontinent.

Reconstruction of phylogenetic history to resolve the subspecies anomaly of Pantherine cats

All charismatic big cats including tiger (Panthera tigris), lion (Panthera leo), leopard (Panthera pardus), snow leopard (Panthera uncial), and jaguar (Panthera onca) are grouped into the subfamily Pantherinae. Several mitogenomic approaches have been employed to reconstruct the phylogenetic history of the Pantherine cats but the phylogeny has remained largely unresolved till date. One of the major reasons for the difficulty in resolving the phylogenetic tree of Pantherine cats is the small sample size. While previous studies included only 5‐10 samples, we have used 43 publically available taxa to reconstruct Pantherine phylogenetic history. Complete mtDNA sequences were used from all individuals excluding the control region (15,489bp). A Bayesian MCMC approach was employed to investigate the divergence times among different Pantherine clades. Both maximum likelihood and Bayesian phylogeny generated a dendrogram: Neofelis nebulosa (Panthera tigris (Panthera onca (Panthera uncia (Panthera leo, Panthera pardus)))), grouping lions with leopards and placing snow leopards as an outgroup to this clade. The phylogeny revealed that lions split from their sister species leopard ~3 Mya and the divergence time between snow leopards and the clade including lions and leopards was estimated to be ~5 Mya. Our study revealed that the morphology-based subspecies designation for both lions and tigers is largely not valid. The estimated tMRCA of 2.9 Mya between Barbary lions and Sub-Saharan African lions depicts the restriction of female-mediated gene flow between the lion populations in the backdrop of the habitat fragmentation taking place from late Pliocene to early to mid-Pleistocene creating islands of forest refugia in central Africa.