Data from: Comparing the effectiveness of metagenomics and metabarcoding for diet analysis of a leaf-feeding monkey (Pygathrix nemaeus)

Fecal samples are of great value as a non-invasive means to gather information on the genetics, distribution, demography, diet, and parasite infestation of endangered species. Direct shotgun sequencing of fecal DNA could give information on these simultaneously, but this approach is largely untested. Here we use two fecal samples to characterize the diet of two Red-Shanked Doucs Langurs (Pygathrix nemaeus) that were fed a known combination of foliage, fruits, vegetables and cereals. Illumina HiSeq sequencing produced ~70 million paired reads per sample, of which ~10000 (0.014%) and ~44000 (0.066%) respectively corresponded to chloroplast genomes. Sequences were matched against a database of available chloroplast ‘barcodes’ for angiosperms. The results were compared with ‘metabarcoding’ using PCR amplification of the P6 loop of trnL. Shotgun sequencing identified 7 and 9 of the likely 16 diet plants, against 6 and 5 plant species identified by metabarcoding. Metabarcoding produced thousands of reads that were consistent with the known diet, but the barcodes were too short to identify several diet plants to genus. Metagenomics could utilize multiple, longer barcodes that combined had greater power of identification, but rare diet items were not recovered. Read numbers for diet species in metagenomic and metabarcoding data were correlated, indicating that both approaches are useful for determining relative sequence abundance. Metagenomic reads were uniformly distributed across the chloroplast genomes; thus if chloroplast genomes were to be used as reference, the precision of identifications and species recovery would improve further. Metagenomics also recovered the host mitochondrial genome and numerous intestinal parasite sequences in addition to generating data useful for characterizing the microbiome.粪便样本作为非侵入性采样手段，在获取濒危物种的遗传学特征、分布范围、种群统计学特征、食性以及寄生虫感染状况等相关信息时具备极高应用价值。对粪便DNA开展直接鸟枪测序（shotgun sequencing）可同时获取上述多类信息，但该方法目前尚未得到广泛验证。本研究选取两份粪便样本，对已知以叶片、果实、蔬菜和谷物组合为食的两只红腿黑叶猴（Pygathrix nemaeus）的食性进行表征。经Illumina HiSeq测序平台测序，每份样本产出约7000万条双端reads，其中分别有约10000条（占比0.014%）和44000条（占比0.066%）序列匹配叶绿体基因组（chloroplast genomes）。将所得序列与公开的被子植物（angiosperms）叶绿体“条形码”数据库进行比对。将上述结果与基于trnL基因P6环PCR扩增的元条形码（metabarcoding）技术所得结果进行对比。鸟枪测序分别鉴定出16种潜在食物植物中的7种和9种，而元条形码技术仅鉴定出6种和5种植物物种。元条形码技术可产生数千条与已知食性相符的reads，但由于条形码序列过短，无法将部分食物植物鉴定到属水平。宏基因组学可利用多条更长的条形码组合，提升物种鉴定效能，但无法检测到稀有食物类群。宏基因组与元条形码数据中食物物种的reads数量呈显著相关，表明两种方法均可用于测定相对序列丰度。宏基因组测序所得reads在叶绿体基因组上分布均匀，因此若以叶绿体基因组作为参考序列，物种鉴定精度与物种检出率可进一步提升。此外，宏基因组测序不仅可获得有助于表征微生物组（microbiome）的数据，还能获取宿主的线粒体基因组以及多种肠道寄生虫序列。