使用元轉錄組估計後生動物的多樣性：從基因到族群

Using metatranscriptomics in estimating metazoan diversity: from genes to communities

羅馬克(Mark Louie Lopez)

指導教授 ： 町田龍二

國立臺灣師範大學/理學院/生命科學系/博士(2022年)

https://doi.org/10.6345/NTNU202200097

摘要

元轉錄組學是一種高通量測序方法，藉由通過隨機測序特定環境條件下樣本的 RNA序列（信使 RNA [mRNA] 和核醣體 RNA [rRNA]）獲取群落的轉錄組信息（第 1 章）。在後生動物群落研究中(如浮游動物研究)使用元轉錄組學並不常見也沒有得到嚴格的驗證。為了解決這個問題,根據生態學代謝理論 (metabolic theory of ecology)和生長數率假設 (growth rate hypothesis),我們提出了一個理論框架來驗證 RNA序列豐度（mRNA 和 rRNA）的異速增長（allometric scaling）。納入影響RNA 產生的因子作為群落多樣性的指標，例如來自元轉錄組學的 RNA 序列讀數通過下一代測序技術可以為代謝率、能量通量和含高磷的RNA 流動提供理論基礎建立模型（第2 章)。基於 PCR 的方法, 我們使用基因組 (gDNA) ,互補 DNA (cDNA) 擴增子以及形態學來估計模擬群落的物種多樣性和組成, 測試並比較了利用元轉錄組學作為表徵浮游動物群落的方法。結果顯示元轉錄組學提供了更好的物種豐富度和組成估計且與利用形態學估計的結果相似（第 3 章）。最後，於翡翠水庫採集的樣本做進一步測試，結果顯示物種多樣性的估計在生物和技術重複之間是一致的。利用元轉錄組學可以檢測數量較少的分類群，並同時解決形態分析所需的繁重工作和分類學專業知識（第 4 章）。在模擬群落和野外樣本中, 利用RNA 序列讀數整合異速增生有助於提升 RNA 序列讀數與物種數量之間的相關性。總體而言，這項研究為在群落生態學研究中使用元轉錄組學提供了一個定量模型，並展示了其作為監測浮游動物群落多樣性的工具的優勢（第 5 章）。

關鍵字

metatranscriptomics ； RNA-sequencing ； DNA metabarcoding ； diversity estimation ； allometric scaling

並列摘要

Metatranscriptomics is a high-throughput sequencing method that allows direct access to community transcriptomic information through random sequencing of RNA (messenger RNA [mRNA] and ribosome RNA [rRNA]) transcripts from samples in specific environmental conditions (Chapter 1). Using metatranscriptomics in studying metazoan communities, like zooplankton research, has been uncommon and not rigorously validated. To address this, we first provide a theoretical framework to integrate the metabolic basis of RNA abundance (mRNA and rRNA) according to the assumptions of the metabolic theory of ecology and growth-rate hypothesis. Considering physiological factors affecting RNA production in molecular tools being used to characterize community diversity, such as RNA transcript reads from metatranscriptomics, could provide a theoretical baseline to model metabolic rate, energy flux, and turnover of phosphorus-rich RNA through next-generation sequencing technology (Chapter 2). Then, we tested and compared metatranscriptomics with PCR-based methods using genomic (gDNA) and complementary DNA (cDNA) amplicons, and morphology-based data for characterizing zooplankton mock communities. Metatranscriptomics provided better species richness and composition estimates that resembled those derived from morphological data (Chapter 3). Lastly, metatranscriptomics was further tested using field-collected samples (Feitsui reservoir), with the results showing consistent species diversity estimates among biological and technical replicates. Metatranscriptomics allowed the detection of less dominant taxa while addressing issues on laborious work and lack of taxonomic expertise needed in morphological analysis (Chapter 4). Moreover, integrating allometric scaling helped improve the predictive models on transcript reads and species biomass both in mock communities and field-collected samples. Overall, this study offers a theoretical framework that could extend the use of metatranscriptomics in characterizing community samples while demonstrating its advantages as an effective tool for monitoring the diversity of metazoan communities (Chapter 5).

並列關鍵字

metatranscriptomics ； RNA-sequencing ； DNA metabarcoding ； diversity estimation ； allometric scaling

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