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Sequencing and Array Technologies · Tutorial 5 of 795

From Sequencing Libraries to Short Reads

Trace how prepared DNA molecules become short sequence records, and learn what those records reveal—and what they do not.

Beginner 11 min read

What You'll Learn

  • Distinguish a DNA fragment, a prepared library molecule, and a base-called read.
  • Explain the roles of adapters and sample indexes in library preparation.
  • Read the sequence and quality lines in a FASTQ record.
  • Interpret Phred quality scores as base-caller error probabilities.
  • Identify stages in the workflow where technical artifacts or errors can arise.
  • Recognize why reads are not automatically independent DNA molecules or complete original fragments.

From DNA Molecules to Recorded Reads

A sequencing file is not a direct photograph of a genome. It contains records produced by a chain of laboratory and computational steps: genomic DNA is broken into fragments, prepared so that a sequencer can process it, read in cycles, and converted by a base caller into strings of letters with quality scores. Each step affects what can eventually be observed. To interpret a short-read file, it helps to keep three objects distinct: the original DNA molecule, the prepared library molecule, and the read recorded by the instrument.

The outline below describes a common short-read workflow, not a universal recipe. Library preparation and sequencing chemistry differ across platforms and protocols. Details such as end repair, amplification, and how a molecule is attached for reading are method-dependent; the general distinction between prepared molecules and base-called reads remains useful across them.

Definition: A DNA fragment is a piece of the sample’s DNA produced by fragmentation or another preparation step. A library molecule is a fragment prepared with sequencing-compatible adapter sequences attached. A read is the sequence of bases called from one end, or from both ends, of a library molecule during sequencing. A read is a measurement of part of a prepared molecule, not necessarily a complete original DNA fragment.

Preparing the Library

In many short-read workflows, DNA is fragmented into pieces that fall within a useful size range. Fragmentation may be physical or enzyme-based. The resulting pieces can have ends that need preparation before adapters can be attached. Depending on the protocol, end repair or other processing may occur, and adapters are then ligated to the fragment ends.

Adapters are known sequences designed to let library molecules interact with the sequencing system. They provide binding or priming sites needed for later steps. Some protocols also attach an index (also called a barcode) to help identify which sample a library came from when multiple samples are processed together. An index is not part of the sample’s genomic sequence. It is a deliberately added label, and its exact location and use depend on the protocol.

Some workflows amplify library molecules before sequencing. Amplification can provide more material, but it can also change the representation of the original fragments: some molecules may be copied more readily than others, and copying may introduce errors. These possibilities arise before a read is produced. They are different from a base-calling error, which is an incorrect letter assigned to a signal during sequencing.

Prepared molecules are made available to the instrument. In a common short-read approach, a molecule is copied or otherwise presented in a form that produces measurable signals over successive sequencing cycles. The instrument records signals; a base caller converts those signals into a sequence of letters and estimates a quality for each called base. In this way, the final record depends both on the DNA in the sample and on preparation, measurement, and computational interpretation.

1
Fragment the DNA.
Break sample DNA into pieces. Fragment length and the method used can affect which pieces are available for subsequent steps.
2
Attach adapters and, where applicable, indexes.
Prepare fragments for sequencing and add sample-identifying labels if the protocol uses them.
3
Sequence and record signals.
The instrument measures signals over cycles as library molecules are read.
4
Call bases and write records.
A base caller assigns letters and per-base quality scores, which are commonly stored with sequence records in FASTQ format.

What a FASTQ Record Contains

A common raw-read file format is FASTQ. Each record has four lines: a line beginning with an identifier, a line containing the called sequence, a separator line, and a line of quality characters. The quality line has one encoded value for each sequence position. The identifier may contain information about the read, instrument run, or sample index, but the precise fields vary. Paired-end data—where both ends of a library molecule are read—are commonly stored as corresponding records in two files or in an interleaved file.

The sequence line records the base calls, usually represented with A, C, G, and T, and sometimes with a character such as N when the base caller does not assign a definite base. The quality line does not give a second sequence. It encodes the base caller’s estimated confidence in each position. The scores use the Phred scale: if \(e\) is the estimated probability that a base call is wrong, then \(Q=-10\log_{10}(e)\), or equivalently \(e=10^{-Q/10}\). These are estimates from the base-calling process, not guarantees about any one base.

Worked Example: Interpreting a Read’s Quality Scores

Suppose a hypothetical FASTQ record has five called bases, ACGTA, with quality scores \(Q=30, 30, 20, 40, 30\), respectively. First convert each score to its estimated error probability using \(e=10^{-Q/10}\).

For the first, second, and fifth positions, \(Q=30\), so \(e=10^{-3}=0.001\) for each. At the third position, \(Q=20\), so \(e=10^{-2}=0.01\). At the fourth position, \(Q=40\), so \(e=10^{-4}=0.0001\).

The sum of these five estimated probabilities is \(0.001+0.001+0.01+0.0001+0.001=0.0131\). If the scores are calibrated estimates, this sum is the expected number of incorrect calls among these five positions. It does not identify which position, if any, is wrong, and it does not establish whether any base is a true genomic variant. The third position has the largest estimated error probability in this example.

A paired-end record represents two reads from opposite ends of the same prepared library molecule. That does not mean the two reads together always reveal every base in the original fragment. If the insert is longer than the combined read lengths, an internal part of the fragment is not directly read; if it is shorter, the reads may overlap. The fragment itself may also include adapter sequence in the recorded read when the sequenced insert ends before a read cycle does. These are consequences of the relationship between library construction and read length, not evidence that a read file contains a complete copy of each source molecule.

Worked Example: What Two 100-Base Reads Can Observe

Consider a hypothetical library with a genomic insert of 180 bases. The sequencing protocol produces a 100-base read from each end of the insert. Assume both reads begin at the insert ends and no bases are lost to low-quality trimming.

The two reads together contain \(100+100=200\) called bases, but the insert is only 180 bases long. The reads therefore overlap by \(200-180=20\) bases. They do not represent 200 distinct insert positions: 20 positions are read from both ends. Their correspondence is two observations from one prepared molecule, not proof of two independent original DNA molecules.

If instead the insert were 230 bases, the same read lengths would cover \(100+100=200\) positions, leaving \(230-200=30\) insert bases between the read ends unobserved. Thus read length and insert length jointly determine which parts of a fragment are directly represented. This arithmetic describes the hypothetical library geometry only; it does not estimate how many times any genomic region was sampled.

Where Technical Problems Can Enter

Errors and distortions can arise at different stages, and the distinction matters when interpreting a read file. Fragmentation may produce a nonuniform set of fragment lengths. Ligation may be inefficient for some molecules, while adapter dimers—adapter sequences joined without a genomic insert—can enter the prepared library. Amplification can favor some library molecules over others or introduce copying errors. During sequencing, signal measurement and base calling can produce incorrect or uncertain calls. These possibilities are not interchangeable: for example, an adapter dimer is a library-preparation artifact, while a low-quality base call is uncertainty about a recorded letter.

Some practical checks follow directly from the record structure. Sequence and quality strings in a valid FASTQ record should have equal lengths, because there must be one quality value per called base. A large amount of adapter sequence in reads can indicate that the read extends beyond a short insert or that adapter removal has not yet been performed. A high proportion of uncertain calls or persistently low per-base scores can flag a sequencing or library-quality concern. These checks can reveal warning signs, but a file alone may not identify the cause; the protocol, run information, and laboratory records provide important context.

Worked Example: Recognizing Adapter Read-Through

Suppose a hypothetical library fragment contains a 72-base genomic insert, followed by adapter sequence, and the instrument records a 100-base read from that end. Assume the read begins at the start of the insert and all 100 cycles produce calls.

The first 72 called positions can correspond to the insert. The remaining \(100-72=28\) positions extend into adapter sequence. The read may therefore contain 72 insert bases and 28 adapter bases, even though its total sequence length is 100. Adapter sequence in this case is not an additional 28 bases of genomic DNA.

If adapter sequence is found near the ends of reads, that observation is consistent with read-through from inserts shorter than the read length. It is not, by itself, proof that fragmentation failed: short inserts can arise in an otherwise functioning workflow. Removing known adapter sequence can clean the recorded sequence, but it cannot recover additional genomic bases that were never present in the insert.

How to Interpret the File—and Its Limits

A FASTQ file answers a focused question: what sequence did the base caller assign to each read, and what quality score did it assign at each position? It does not, on its own, say exactly which original genomic molecule produced every record, whether every molecule in the sample was equally likely to enter the library, or whether a called difference from a reference is biologically real. Those questions require additional processing and evidence. For now, the important point is that sequence records are observations generated by a workflow, not unmediated copies of the sample’s DNA.

Short-read sequencing also differs from a genotyping array. An array measures signals at selected sites determined by its probe design; a sequencing read records a short stretch of called bases from a prepared molecule. Neither measurement is free of technical limitations, but their measurement mechanisms and resulting data are different. A read should not be treated as an array genotype call, and an array’s selected probe set should not be mistaken for a set of sequence reads.

Paired-end sequencing is one option when information from both ends of a library molecule is useful; single-end sequencing records only one end. Paired-end reads can provide more observations of a fragment’s ends, but they do not automatically reveal the unsequenced middle of a long insert. Similarly, increasing read length may change how much of an individual fragment is observed, but it does not eliminate biases introduced during library construction or uncertainty in base calling.

Common pitfall: “A 100-base read is 100 bases of the original genome, and every record is an independent original molecule.” This reasoning is not justified. A read can include adapter sequence, and multiple records can arise from copies of the same prepared fragment. Interpret the sequence and quality as base-caller outputs from library molecules, and use protocol information to understand what those outputs represent.

Check Your Understanding

Answer each question, then compare your reasoning with the solutions below.

  1. What is the difference between an adapter and a genomic insert in a prepared library molecule?
  2. A base has a Phred score of \(Q=20\). What estimated error probability does that score correspond to?
  3. A hypothetical insert is 150 bases long, and paired-end sequencing produces 75 bases from each end. How many insert positions are represented, and are any positions read twice?
  4. A 90-base insert is sequenced for 110 cycles from one end. Under the stated assumption that the read starts at the insert and all cycles produce calls, how many calls can extend into adapter sequence?
  5. Why does a high-quality score not prove that a called base is a true genomic variant?

Solutions. (1) The genomic insert is the sample-derived DNA fragment; adapters are added sequences that help prepare and process the fragment for sequencing. (2) \(e=10^{-20/10}=10^{-2}=0.01\), or an estimated 1% error probability for that call. (3) The reads contain \(75+75=150\) bases in total, matching the 150-base insert, so under the stated assumptions all insert positions are represented once, with no overlap. (4) \(110-90=20\) calls can extend into adapter sequence. (5) The score describes the base caller’s estimated probability of an incorrect call at that position. It does not establish the biological origin of the sequence or whether a difference from a reference is real; those conclusions require further analysis and evidence.

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