The Resolution Problem

Global ancestry DNA tests have a resolution problem when it comes to the Indian subcontinent. Over 1.4 billion people get lumped into a single label: "South Asian." That is like telling a European they are simply "European" — erasing the difference between a Sicilian and a Swede.

If you have taken a test from 23andMe, AncestryDNA, or MyHeritage, you have likely seen this firsthand. The result tells you where you already know you are from, and nothing deeper. This is not a limitation of the technology — it is a limitation of the reference data these companies use.

Reference Panel Bias

The root cause is reference panel bias. Most commercial tests are built on panels dominated by European, East Asian, and African populations. South Asian representation is thin, and Indian genetic diversity — shaped by 65,000 years of migration, the caste system, and linguistic endogamy — is almost entirely invisible in their models.

A reference panel is the dataset against which your DNA is compared. If the panel does not contain distinct samples from Punjabis, Marathis, Tamils, Bengalis, and hundreds of other communities, the algorithm has no basis for telling them apart. It defaults to the broadest label it can assign with confidence: "South Asian."

India's Genetic Diversity Is Extraordinary

Indian populations carry distinct genetic signatures at the state, community, and even sub-community level. The major sources of this diversity include:

• Ancestral North Indian (ANI) & Ancestral South Indian (ASI) — a gradient of admixture that varies by region and community, first characterized by David Reich's lab
• Steppe pastoralist admixture — arriving ~3,500 years ago and concentrated in northern and upper-caste groups
• Harappan-era farmer DNA — the genetic signature of the Indus Valley Civilization, widely distributed across modern Indians
• Austroasiatic and Tibeto-Burman components — present in eastern and northeastern populations
• Endogamy effects — millennia of community-level marriage practices have created genetically distinct clusters numbering in the thousands

The technology exists to resolve these — it just has not been applied to India at scale by global companies, because the commercial incentive has historically been elsewhere.

What Indian-Focused Ancestry Testing Reveals

This is exactly the problem that Helixline was built to solve. By constructing reference panels from 4,500+ Indian community clusters and mapping state-level ancestry components, Helixline's ancestry DNA test provides the resolution that global tests cannot.

Instead of "100% South Asian," you get a breakdown of your ANI-ASI ratio, your haplogroup lineages (maternal and paternal), Harappan farmer DNA percentage, and community-level ancestry matching. This is the difference between a blurry photograph and a high-resolution scan.

The Bottom Line

If you have ever received a "100% South Asian" result and felt it told you nothing — you were right. It is not that your ancestry is simple. It is that the test was not built for you. Indian-focused ancestry testing, built on Indian reference panels, is the answer.

Your DNA Is a Migration Record

Every Indian carries a genetic record of ancient migrations. Haplogroups — inherited through the maternal (mtDNA) and paternal (Y-chromosome) lines — reveal deep ancestry that predates surnames, languages, and modern borders. They are molecular fossils, unchanged markers passed down for tens of thousands of years.

Unlike autosomal DNA, which gets shuffled every generation, haplogroups follow strict inheritance: your Y-chromosome haplogroup comes from your father's father's father (and so on), while your mitochondrial haplogroup traces your mother's mother's mother. This makes them uniquely powerful for tracing ancient migration routes.

Major Y-Chromosome Haplogroups in India

• R1a (R-M17) — The most discussed haplogroup in Indian genetics. Associated with Steppe pastoralist migrations arriving ~3,500 years ago. Found at high frequencies in Indo-European speaking populations, particularly in northern India and among Brahmin communities. However, its presence across India is far more nuanced than simple invasion narratives suggest.
• H (H-M69) — One of the oldest Y-chromosome lineages in India, with deep roots in the subcontinent spanning 30,000+ years. Found across diverse Indian communities, with higher frequencies in tribal and Dravidian-speaking populations.
• L (L-M20) — Linked to pre-Steppe indigenous populations and potentially connected to the Indus Valley Civilization. Found in significant frequencies in western and southern India.
• J2 (J-M172) — Connected to Neolithic farmer expansions from the Fertile Crescent. Found in western India and parts of the Deccan, often correlated with agriculturalist communities.
• O (O-M175) — Found primarily in northeastern India and among Austroasiatic-speaking groups, connecting these populations to East and Southeast Asian migration routes.

Maternal Haplogroups Tell a Deeper Story

On the maternal side, M, R, and U haplogroups tell a 50,000-year story of settlement and diversification across the subcontinent. Haplogroup M is particularly significant — it is one of the oldest lineages outside of Africa and is found at remarkably high frequencies across India, suggesting very early coastal migration routes.

Subclades like U2, U7, and R5 are almost exclusively South Asian, providing fine-grained information about regional ancestry that no global test can match.

The ANI-ASI Framework

The ANI-ASI framework, first described by David Reich's lab in a landmark 2009 paper, shows that most Indians are a mixture of two ancient populations:

• Ancestral North Indian (ANI) — Genetically closer to Central Asians, Middle Easterners, and Europeans. Represents admixture from Steppe pastoralists and possibly earlier western migrations.
• Ancestral South Indian (ASI) — A deeply divergent lineage unique to the Indian subcontinent, with no close relatives anywhere else in the world. This is the genetic signature of the earliest settlers of India.

The ratio of ANI to ASI varies dramatically by region and community. Northern and upper-caste groups tend to have higher ANI proportions, while southern and tribal groups tend to have higher ASI. But every Indian carries both components — the question is the ratio, and that ratio tells a rich story about your family's deep history.

Mapping Your Place in 65,000 Years of History

Platforms like Helixline now map these ANI-ASI ratios at the individual level, alongside haplogroup determination and Harappan-era farmer DNA matching. For anyone curious about how their family fits into 65,000 years of Indian genetic history, DNA ancestry testing focused on India can provide answers that no global test ever could.

The science is no longer limited to academic papers and research labs. It is now accessible to anyone with a DNA sample and a curiosity about where they came from.

The Challenge of South Asian Genomes

Ancestry analysis at population scale requires a robust bioinformatics pipeline that can handle genotyping arrays, imputation, quality control, and admixture modeling — all tuned for the unique characteristics of South Asian genomes. The high levels of endogamy, complex population structure, and underrepresentation in global databases make Indian genomes particularly challenging to analyze accurately.

Standard pipelines developed for European or East Asian cohorts often fail silently on Indian data, producing results that look plausible but are fundamentally inaccurate. Building a pipeline that works for India means rethinking assumptions at every step.

Step 1: Genotyping & Sample-Level QC

The typical workflow begins with genotyping on SNP arrays. The Illumina Global Screening Array (GSA) is the most common choice, offering good coverage of common variants across diverse populations. After genotyping, rigorous sample-level quality control is essential:

• Call rate filtering — Samples with less than 98% genotyping rate are removed
• Sex check — Verify reported sex matches X-chromosome heterozygosity
• Heterozygosity outlier removal — Extreme heterozygosity can indicate sample contamination or technical artifacts
• Relatedness pruning with KING — Remove cryptic duplicates and close relatives that can bias downstream analysis

Step 2: Variant-Level QC

Variant-level QC requires special attention for Indian populations:

• Hardy-Weinberg filtering — Must be applied carefully in structured populations. Strict HWE thresholds that work for outbred European cohorts can falsely flag genuine population structure in Indian data
• Minor allele frequency thresholds — Set appropriately for the target population; variants common in India may be rare globally and vice versa
• Strand alignment — Ensure all variants are oriented to the same reference genome strand, resolving ambiguous A/T and C/G SNPs

Step 3: Imputation

Imputation against the 1000 Genomes or TOPMed panels fills in ungenotyped variants, dramatically increasing the number of analyzable markers. However, accuracy drops significantly for rare variants in underrepresented populations. For Indian genomes, imputation accuracy at rare variants (MAF < 1%) can be 20-30% lower than for European samples using the same reference panel.

This is where custom Indian reference panels become essential. Panels built from whole-genome sequencing of diverse Indian communities capture population-specific variants and haplotype structures that global panels miss entirely.

Step 4: Population Structure Analysis

After imputation, the core analysis begins. Principal component analysis (PCA) reveals the major axes of genetic variation, while ADMIXTURE modeling decomposes individual genomes into ancestral components:

• PCA — For Indian data, the first two PCs typically separate the ANI-ASI gradient, while subsequent PCs resolve Austroasiatic, Tibeto-Burman, and regional signals
• ADMIXTURE modeling — K=4 to K=8 typically captures the major ancestral components in Indian populations: ANI, ASI, Austroasiatic, and Tibeto-Burman signals. Cross-validation helps select the optimal K
• f-statistics and formal admixture tests — Provide rigorous statistical evidence for admixture events and population relationships

The Helixline Pipeline

This pipeline — refined over years of work on Indian genetic datasets — forms the backbone of the Helixline ancestry platform. Every sample processed through Helixline's ancestry test runs through these steps, combined with proprietary reference panels covering 4,500+ Indian community clusters, to deliver state-level and community-level ancestry resolution.

The result is not a vague continental label, but a detailed genetic portrait: your ANI-ASI ratio, haplogroup assignments, Harappan farmer DNA percentage, and matches to specific Indian community reference clusters — all computed through a pipeline purpose-built for the world's most genetically diverse subcontinent.