Deep whole-genome sequencing of 100 Malays

The 1000 Genomes Project is the largest collection of full human genomes currently available, but most of its 2.5k samples have been sequenced at low coverage. One downside of this is that infrequent variants are often missed. If an individual is polymorphic at some site, then the chance of detecting this polymorphism increases with the number of reads covering that site. If a number of individuals are sampled, then polymorphisms that are common in the population will probably be detected in a few individuals even if a low number of reads is used for each of them; but, if they are infrequent, then they are more likely to be missed. Hence, low-coverage sequencing of population samples will tend to find common variants and will tend to miss less common variants relative to high-coverage sequencing.

This idea is intuitively correct, but the question of the added power of high-coverage sequencing to detect variants can only be addressed by giving the same individuals both low- and high-coverage sequencing. This is the topic of a new paper in AJHG which creates a useful comparison benchmark for the performance of the two types of sequencing methods. High-coverage sequencing may be needed for things like disease studies (because deleterious alleles tend to be low-frequency), or the study of recent human demography (because recent population growth has resulted in an abundance of low-frequency SNPs that have not had enough time to reach a high population frequency yet).

AJHG dx.doi.org/10.1016/j.ajhg.2012.12.005

Deep Whole-Genome Sequencing of 100 Southeast Asian Malays

Lai-Ping Wong et al.


Whole-genome sequencing across multiple samples in a population provides an unprecedented opportunity for comprehensively characterizing the polymorphic variants in the population. Although the 1000 Genomes Project (1KGP) has offered brief insights into the value of population-level sequencing, the low coverage has compromised the ability to confidently detect rare and low-frequency variants. In addition, the composition of populations in the 1KGP is not complete, despite the fact that the study design has been extended to more than 2,500 samples from more than 20 population groups. The Malays are one of the Austronesian groups predominantly present in Southeast Asia and Oceania, and the Singapore Sequencing Malay Project (SSMP) aims to perform deep whole-genome sequencing of 100 healthy Malays. By sequencing at a minimum of 30? coverage, we have illustrated the higher sensitivity at detecting low-frequency and rare variants and the ability to investigate the presence of hotspots of functional mutations. Compared to the low-pass sequencing in the 1KGP, the deeper coverage allows more functional variants to be identified for each person. A comparison of the fidelity of genotype imputation of Malays indicated that a population-specific reference panel, such as the SSMP, outperforms a cosmopolitan panel with larger number of individuals for common SNPs. For lower-frequency (less than 5%) markers, a larger number of individuals might have to be whole-genome sequenced so that the accuracy currently afforded by the 1KGP can be achieved. The SSMP data are expected to be the benchmark for evaluating the value of deep population-level sequencing versus low-pass sequencing, especially in populations that are poorly represented in population-genetics studies.



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ADMIXTURE on the shores of the Indian Ocean

I have applied Multidimensional Scaling and ADMIXTURE on a dataset of 15 populations:

Cambodians, Papuan, NAN_Melanesian, Gujarati, Malayan, Paniya, North_Kannadi, Sakilli, Singaporean Indians, Singaporean Chinese, Singaporean Malay, Yemenese, Saudis, Maasai, Ethiopians

These were collected from HGDP, Behar et al. (2010), HapMap-3, and the Singapore Genome Variation Project. There are 423 individuals in general (I've used samples of 25 individuals from the HapMap populations).

Here is the MDS plot:

At the bottom are the Papuans, relatively unadmixed Australoids. Close to them, but deviating towards East Eurasians are the NAN Melanesians; these are the Nasioi, Papuan speakers from Bougainville, which they inhabit together with Austronesian speakers.

At the top left are the Singaporean Chinese (CHS) who are Mongoloids. Deviating from them towards Indians are the Cambodians, a Southeast Asian group which according to physical anthropology is a basically Mongoloid population, but admixed with a pre-Mongoloid southern population element similar to that which has been preserved in India. Similar to them are the Singaporean Malay (MAS), another population that is basically Mongoloid but has absorbed Indian-like population elements.

The Singaporean Indians (INS), the North Kannada, the Sakilli and the Gujarati (GIH25) form the third population element in the region of interest.

The other two are the Caucasoids, represented here by the Saudis, with the Yemenese spread toward Africa and the more Caucasoid-admixed Ethiopians and the relatively unadmixed Maasai (MKK25).

These are the main population elements of our region of interest: Ethiopids and Australoids framing the Ocean on the west and east; the South Asians occupying India, and the Mongoloids occupying Southeast Asia, having absorbed the Indian-like former inhabitants of the region.

Here is a blowup of the middle part of the MDS plot, focusing on the Indians:

It's fairly clear that North Kannada and Sakilli (South Indians) occupy a place that is furthest from Caucasoids, while Gujarati and Singaporean Indians are positioned towards Caucasoids (to the top-right).

Let's now turn to ADMIXTURE to confirm the visual impression from the MDS:

Notice the following components:

1. Light blue, Indian
2. Dark blue, East African
3. Light green, Southeast Asian
4. Dark green, Chinese Mongoloid
5. Pink, Arabian Caucasoid
6. Red, Australoid

Finally, here is the table of Fst distances between these 6 inferred components:

Notice the small distance (0.023) between Chinese and Southeast Asian Mongoloids. The Indian component is equidistant between Caucasoids and Mongoloids, but as the MDS plot makes clear, and as the study of Y-chromosome and mtDNA polymorphisms have shown, the distinctive component in Indians is sui generis and not the result of admixture between Caucasoids and Mongoloids. And, finally, the Australoid component is clearly distant from all of the above.