Motivated by computing duplication patterns in sequences, a new problem called the longest letter-duplicated subsequence (LLDS) is proposed. Given a sequence S of length n, a letter-duplicated subsequence is a subsequence of S in the form of (x_1^{d_1}x_2^{d_2}ldots x_k^{d_k}) with (x_iin Sigma ), (x_jne x_{j+1}) and (d_ige 2) for all i in [k] and j in ([k-1]). A linear time algorithm for computing a longest letter-duplicated subsequence (LLDS) of S can be easily obtained. In this paper, we focus on two variants of this problem: (1) ‘all-appearance’ version, i.e., all letters in (Sigma ) must appear in the solution, and (2) the weighted version. For the former, we obtain dichotomous results: We prove that, when each letter appears in S at least 4 times, the problem and a relaxed version on feasibility testing (FT) are both NP-hard. The reduction is from ((3^+,1,2^-))-SAT, where all 3-clauses (i.e., containing 3 lals) are monotone (i.e., containing only positive literals) and all 2-clauses contain only negative literals. We then show that when each letter appears in S at most 3 times, then the problem admits an O(n) time algorithm. Finally, we consider the weighted version, where the weight of a block (x_i^{d_i} (d_ige 2)) could be any positive function which might not grow with (d_i). We give a non-trivial (O(n^2)) time dynamic programming algorithm for this version, i.e., computing an LD-subsequence of S whose weight is maximized.